WorldWideScience

Sample records for hierarchical social networks

  1. Epidemic spreading in a hierarchical social network.

    Science.gov (United States)

    Grabowski, A; Kosiński, R A

    2004-09-01

    A model of epidemic spreading in a population with a hierarchical structure of interpersonal interactions is described and investigated numerically. The structure of interpersonal connections is based on a scale-free network. Spatial localization of individuals belonging to different social groups, and the mobility of a contemporary community, as well as the effectiveness of different interpersonal interactions, are taken into account. Typical relations characterizing the spreading process, like a range of epidemic and epidemic curves, are discussed. The influence of preventive vaccinations on the spreading process is investigated. The critical value of preventively vaccinated individuals that is sufficient for the suppression of an epidemic is calculated. Our results are compared with solutions of the master equation for the spreading process and good agreement of the character of this process is found.

  2. Category theoretic analysis of hierarchical protein materials and social networks.

    Directory of Open Access Journals (Sweden)

    David I Spivak

    Full Text Available Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we describe an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a "concept web" or "semantic network" except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other olog. We consider simple cases of beta-helical and amyloid-like protein filaments subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog for the social network feature identical category-theoretic representations, and we proceed to precisely explicate the analogy or isomorphism between them. The examples presented here demonstrate that the intrinsic nature of a complex system, which in particular includes a precise relationship between structure and function at different hierarchical levels, can be effectively represented by an olog. This, in turn, allows for comparative studies between disparate materials or fields of application, and results in novel approaches to derive functionality in the design of de novo hierarchical systems. We discuss opportunities and challenges associated with the description of complex biological materials by using ologs as a powerful tool for analysis and design in the context of materiomics, and we present the potential impact of this approach for engineering, life sciences, and medicine.

  3. Predicting Hierarchical Structure in Small World Social Networks

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar

    2009-01-01

    Typisk analytisk foranstaltninger i grafteori gerne grad centralitet, betweenness og nærhed centralities er meget almindelige og har lang tradition for deres vellykkede brug. Men modellering af skjult, terrorister eller kriminelle netværk gennem sociale grafer ikke rigtig give den hierarkiske str...

  4. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... with changing and increasing demands. Two-layer networks consist of one backbone network, which interconnects cluster networks. The clusters consist of nodes and links, which connect the nodes. One node in each cluster is a hub node, and the backbone interconnects the hub nodes of each cluster and thus...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks...

  5. Biased trapping issue on weighted hierarchical networks

    Indian Academy of Sciences (India)

    archical networks which are based on the classic scale-free hierarchical networks. ... Weighted hierarchical networks; weight-dependent walks; mean first passage ..... The weighted networks can mimic some real-world natural and social systems to ... the Priority Academic Program Development of Jiangsu Higher Education ...

  6. The SIS Model of Epidemic Spreading in a Hierarchical Social Network

    International Nuclear Information System (INIS)

    Grabowski, A.; Kosinski, R.A.

    2005-01-01

    The phenomenon of epidemic spreading in a population with a hierarchical structure of interpersonal interactions is described and investigated numerically. The SIS model with temporal immunity to a disease and a time of incubation is used. In our model spatial localization of individuals belonging to different social groups, effectiveness of different interpersonal interactions and the mobility of a contemporary community are taken into account. The structure of interpersonal connections is based on a scale-free network. The influence of the structure of the social network on typical relations characterizing the spreading process, like a range of epidemic and epidemic curves, is discussed. The probability that endemic state occurs is also calculated. Surprisingly it occurs, that less contagious diseases has greater chance to survive. The influence of preventive vaccinations on the spreading process is investigated and critical range of vaccinations that is sufficient for the suppression of an epidemic is calculated. Our results of numerical calculations are compared with the solutions of the master equation for the spreading process, and good agreement is found. (author)

  7. A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Eva González-Parada

    2017-01-01

    Full Text Available Autonomous mobile nodes in mobile wireless sensor networks (MWSN allow self-deployment and self-healing. In both cases, the goals are: (i to achieve adequate coverage; and (ii to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage.

  8. A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks.

    Science.gov (United States)

    González-Parada, Eva; Cano-García, Jose; Aguilera, Francisco; Sandoval, Francisco; Urdiales, Cristina

    2017-01-09

    Autonomous mobile nodes in mobile wireless sensor networks (MWSN) allow self-deployment and self-healing. In both cases, the goals are: (i) to achieve adequate coverage; and (ii) to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage.

  9. Visualization of Social Networks

    NARCIS (Netherlands)

    Boertjes, E.M.; Kotterink, B.; Jager, E.J.

    2011-01-01

    Current visualizations of social networks are mostly some form of node-link diagram. Depending on the type of social network, this can be some treevisualization with a strict hierarchical structure or a more generic network visualization.

  10. Detecting Hierarchical Structure in Networks

    DEFF Research Database (Denmark)

    Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard

    2012-01-01

    Many real-world networks exhibit hierarchical organization. Previous models of hierarchies within relational data has focused on binary trees; however, for many networks it is unknown whether there is hierarchical structure, and if there is, a binary tree might not account well for it. We propose...... a generative Bayesian model that is able to infer whether hierarchies are present or not from a hypothesis space encompassing all types of hierarchical tree structures. For efficient inference we propose a collapsed Gibbs sampling procedure that jointly infers a partition and its hierarchical structure....... On synthetic and real data we demonstrate that our model can detect hierarchical structure leading to better link-prediction than competing models. Our model can be used to detect if a network exhibits hierarchical structure, thereby leading to a better comprehension and statistical account the network....

  11. Hierarchical Winner-Take-All Particle Swarm Optimization Social Network for Neural Model Fitting

    Science.gov (United States)

    Coventry, Brandon S.; Parthasarathy, Aravindakshan; Sommer, Alexandra L.; Bartlett, Edward L.

    2016-01-01

    Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models. PMID:27726048

  12. Hierarchical winner-take-all particle swarm optimization social network for neural model fitting.

    Science.gov (United States)

    Coventry, Brandon S; Parthasarathy, Aravindakshan; Sommer, Alexandra L; Bartlett, Edward L

    2017-02-01

    Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models.

  13. Modular networks with hierarchical organization

    Indian Academy of Sciences (India)

    Several networks occurring in real life have modular structures that are arranged in a hierarchical fashion. In this paper, we have proposed a model for such networks, using a stochastic generation method. Using this model we show that, the scaling relation between the clustering and degree of the nodes is not a necessary ...

  14. Loops in hierarchical channel networks

    Science.gov (United States)

    Katifori, Eleni; Magnasco, Marcelo

    2012-02-01

    Nature provides us with many examples of planar distribution and structural networks having dense sets of closed loops. An archetype of this form of network organization is the vasculature of dicotyledonous leaves, which showcases a hierarchically-nested architecture. Although a number of methods have been proposed to measure aspects of the structure of such networks, a robust metric to quantify their hierarchical organization is still lacking. We present an algorithmic framework that allows mapping loopy networks to binary trees, preserving in the connectivity of the trees the architecture of the original graph. We apply this framework to investigate computer generated and natural graphs extracted from digitized images of dicotyledonous leaves and animal vasculature. We calculate various metrics on the corresponding trees and discuss the relationship of these quantities to the architectural organization of the original graphs. This algorithmic framework decouples the geometric information from the metric topology (connectivity and edge weight) and it ultimately allows us to perform a quantitative statistical comparison between predictions of theoretical models and naturally occurring loopy graphs.

  15. Stability of glassy hierarchical networks

    Science.gov (United States)

    Zamani, M.; Camargo-Forero, L.; Vicsek, T.

    2018-02-01

    The structure of interactions in most animal and human societies can be best represented by complex hierarchical networks. In order to maintain close-to-optimal function both stability and adaptability are necessary. Here we investigate the stability of hierarchical networks that emerge from the simulations of an organization type with an efficiency function reminiscent of the Hamiltonian of spin glasses. Using this quantitative approach we find a number of expected (from everyday observations) and highly non-trivial results for the obtained locally optimal networks, including, for example: (i) stability increases with growing efficiency and level of hierarchy; (ii) the same perturbation results in a larger change for more efficient states; (iii) networks with a lower level of hierarchy become more efficient after perturbation; (iv) due to the huge number of possible optimal states only a small fraction of them exhibit resilience and, finally, (v) ‘attacks’ targeting the nodes selectively (regarding their position in the hierarchy) can result in paradoxical outcomes.

  16. Epidemics and dimensionality in hierarchical networks

    Science.gov (United States)

    Zheng, Da-Fang; Hui, P. M.; Trimper, Steffen; Zheng, Bo

    2005-07-01

    Epidemiological processes are studied within a recently proposed hierarchical network model using the susceptible-infected-refractory dynamics of an epidemic. Within the network model, a population may be characterized by H independent hierarchies or dimensions, each of which consists of groupings of individuals into layers of subgroups. Detailed numerical simulations reveal that for H>1, global spreading results regardless of the degree of homophily of the individuals forming a social circle. For H=1, a transition from global to local spread occurs as the population becomes decomposed into increasingly homophilous groups. Multiple dimensions in classifying individuals (nodes) thus make a society (computer network) highly susceptible to large-scale outbreaks of infectious diseases (viruses).

  17. Analyzing security protocols in hierarchical networks

    DEFF Research Database (Denmark)

    Zhang, Ye; Nielson, Hanne Riis

    2006-01-01

    Validating security protocols is a well-known hard problem even in a simple setting of a single global network. But a real network often consists of, besides the public-accessed part, several sub-networks and thereby forms a hierarchical structure. In this paper we first present a process calculus...... capturing the characteristics of hierarchical networks and describe the behavior of protocols on such networks. We then develop a static analysis to automate the validation. Finally we demonstrate how the technique can benefit the protocol development and the design of network systems by presenting a series...

  18. Deep hierarchical attention network for video description

    Science.gov (United States)

    Li, Shuohao; Tang, Min; Zhang, Jun

    2018-03-01

    Pairing video to natural language description remains a challenge in computer vision and machine translation. Inspired by image description, which uses an encoder-decoder model for reducing visual scene into a single sentence, we propose a deep hierarchical attention network for video description. The proposed model uses convolutional neural network (CNN) and bidirectional LSTM network as encoders while a hierarchical attention network is used as the decoder. Compared to encoder-decoder models used in video description, the bidirectional LSTM network can capture the temporal structure among video frames. Moreover, the hierarchical attention network has an advantage over single-layer attention network on global context modeling. To make a fair comparison with other methods, we evaluate the proposed architecture with different types of CNN structures and decoders. Experimental results on the standard datasets show that our model has a more superior performance than the state-of-the-art techniques.

  19. Hierarchical spatial organization of geographical networks

    International Nuclear Information System (INIS)

    Travencolo, Bruno A N; Costa, Luciano da F

    2008-01-01

    In this work, we propose a hierarchical extension of the polygonality index as the means to characterize geographical planar networks. By considering successive neighborhoods around each node, it is possible to obtain more complete information about the spatial order of the network at progressive spatial scales. The potential of the methodology is illustrated with respect to synthetic and real geographical networks

  20. Ultrafast Hierarchical OTDM/WDM Network

    Directory of Open Access Journals (Sweden)

    Hideyuki Sotobayashi

    2003-12-01

    Full Text Available Ultrafast hierarchical OTDM/WDM network is proposed for the future core-network. We review its enabling technologies: C- and L-wavelength-band generation, OTDM-WDM mutual multiplexing format conversions, and ultrafast OTDM wavelengthband conversions.

  1. The influence of gender, age, matriline and hierarchical rank on individual social position, role and interactional patterns in Macaca sylvanus at ‘La Forêt des singes’: A multilevel social network approach

    Directory of Open Access Journals (Sweden)

    Sebastian OROZCO SOSA

    2016-04-01

    Full Text Available A society is a complex system composed of individuals that can be characterized by their own attributes that influence their behaviors. In this study, a specific analytical protocol based on social network analysis was adopted to investigate the influence of four attributes (gender, age, matriline, and hierarchical rank on affiliative (allogrooming and agonistic networks in a non-human primate species, Macaca sylvanus, at the park La Forêt des Singes in France. The results show significant differences with respect to the position (i.e. centric, peripheral and role (i.e. implication in the network cohesiveness of an individual within a social network and hence interactional patterns. Females are more central, more active, and have a denser ego network in the affiliative social network tan males; thus, they contribute in a greater way to the cohesive structure of the network. High-ranking individuals are likely to receive fewer agonistic behaviors than low-ranking individuals, and high-ranking females receive more allogrooming. I also observe homophily for affiliative interactions regarding all attributes and homophily for agonistic interactions regarding gender and age. Revealing the positions, the roles, and the interactional behavioral patterns of individuals can help understand the mechanisms that shape the overall structure of a social network.

  2. The Influence of Gender, Age, Matriline and Hierarchical Rank on Individual Social Position, Role and Interactional Patterns in Macaca sylvanus at 'La Forêt des Singes': A Multilevel Social Network Approach.

    Science.gov (United States)

    Sosa, Sebastian

    2016-01-01

    A society is a complex system composed of individuals that can be characterized by their own attributes that influence their behaviors. In this study, a specific analytical protocol based on social network analysis was adopted to investigate the influence of four attributes (gender, age, matriline, and hierarchical rank) on affiliative (allogrooming) and agonistic networks in a non-human primate species, Macaca sylvanus, at the park La Forêt des Singes in France. The results show significant differences with respect to the position (i.e., centric, peripheral) and role (i.e., implication in the network cohesiveness) of an individual within a social network and hence interactional patterns. Females are more central, more active, and have a denser ego network in the affiliative social network tan males; thus, they contribute in a greater way to the cohesive structure of the network. High-ranking individuals are likely to receive fewer agonistic behaviors than low-ranking individuals, and high-ranking females receive more allogrooming. I also observe homophily for affiliative interactions regarding all attributes and homophily for agonistic interactions regarding gender and age. Revealing the positions, the roles, and the interactional behavioral patterns of individuals can help understand the mechanisms that shape the overall structure of a social network.

  3. Attachment and social networks.

    Science.gov (United States)

    Gillath, Omri; C Karantzas, Gery; Lee, Juwon

    2018-02-21

    The current review covers two lines of research linking attachment and social networks. One focuses on attachment networks (the people who fulfill one's attachment needs), examining composition and age-related differences pertaining to these networks. The other line integrates attachment with social network analysis to investigate how individual differences in adult attachment are associated with the management and characteristics (e.g., density, multiplexity, and centrality) of people's social networks. We show that most people's attachment networks are small and hierarchical, with one figure being the primary attachment figure (often a mother or romantic partner, depending on age). Furthermore, attachment style predicts network characteristics and management, such that insecurity is associated with less closeness, multiplexity, centrality, and poorer management (less maintenance, more dissolution). Copyright © 2018 Elsevier Ltd. All rights reserved.

  4. Noise enhances information transfer in hierarchical networks.

    Science.gov (United States)

    Czaplicka, Agnieszka; Holyst, Janusz A; Sloot, Peter M A

    2013-01-01

    We study the influence of noise on information transmission in the form of packages shipped between nodes of hierarchical networks. Numerical simulations are performed for artificial tree networks, scale-free Ravasz-Barabási networks as well for a real network formed by email addresses of former Enron employees. Two types of noise are considered. One is related to packet dynamics and is responsible for a random part of packets paths. The second one originates from random changes in initial network topology. We find that the information transfer can be enhanced by the noise. The system possesses optimal performance when both kinds of noise are tuned to specific values, this corresponds to the Stochastic Resonance phenomenon. There is a non-trivial synergy present for both noisy components. We found also that hierarchical networks built of nodes of various degrees are more efficient in information transfer than trees with a fixed branching factor.

  5. Hierarchical modularity in human brain functional networks

    Directory of Open Access Journals (Sweden)

    David Meunier

    2009-10-01

    Full Text Available The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or “modules-within-modules” decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions.

  6. Modular networks with hierarchical organization: The dynamical ...

    Indian Academy of Sciences (India)

    Most of the complex systems seen in real life also have associated dynamics [10], and the ... another example, this time a hierarchical structure, viz., the Cayley tree with b ..... natural constraints operating on networks in real life, such as the ...

  7. Social networks

    CERN Document Server

    Etaner-Uyar, A Sima

    2014-01-01

    The present volume provides a comprehensive resource for practitioners and researchers alike-both those new to the field as well as those who already have some experience. The work covers Social Network Analysis theory and methods with a focus on current applications and case studies applied in various domains such as mobile networks, security, machine learning and health. With the increasing popularity of Web 2.0, social media has become a widely used communication platform. Parallel to this development, Social Network Analysis gained in importance as a research field, while opening up many

  8. Hierarchical Network Design Using Simulated Annealing

    DEFF Research Database (Denmark)

    Thomadsen, Tommy; Clausen, Jens

    2002-01-01

    networks are described and a mathematical model is proposed for a two level version of the hierarchical network problem. The problem is to determine which edges should connect nodes, and how demand is routed in the network. The problem is solved heuristically using simulated annealing which as a sub......-algorithm uses a construction algorithm to determine edges and route the demand. Performance for different versions of the algorithm are reported in terms of runtime and quality of the solutions. The algorithm is able to find solutions of reasonable quality in approximately 1 hour for networks with 100 nodes....

  9. Mitigating Herding in Hierarchical Crowdsourcing Networks.

    Science.gov (United States)

    Yu, Han; Miao, Chunyan; Leung, Cyril; Chen, Yiqiang; Fauvel, Simon; Lesser, Victor R; Yang, Qiang

    2016-12-05

    Hierarchical crowdsourcing networks (HCNs) provide a useful mechanism for social mobilization. However, spontaneous evolution of the complex resource allocation dynamics can lead to undesirable herding behaviours in which a small group of reputable workers are overloaded while leaving other workers idle. Existing herding control mechanisms designed for typical crowdsourcing systems are not effective in HCNs. In order to bridge this gap, we investigate the herding dynamics in HCNs and propose a Lyapunov optimization based decision support approach - the Reputation-aware Task Sub-delegation approach with dynamic worker effort Pricing (RTS-P) - with objective functions aiming to achieve superlinear time-averaged collective productivity in an HCN. By considering the workers' current reputation, workload, eagerness to work, and trust relationships, RTS-P provides a systematic approach to mitigate herding by helping workers make joint decisions on task sub-delegation, task acceptance, and effort pricing in a distributed manner. It is an individual-level decision support approach which results in the emergence of productive and robust collective patterns in HCNs. High resolution simulations demonstrate that RTS-P mitigates herding more effectively than state-of-the-art approaches.

  10. Hierarchical regular small-world networks

    International Nuclear Information System (INIS)

    Boettcher, Stefan; Goncalves, Bruno; Guclu, Hasan

    2008-01-01

    Two new networks are introduced that resemble small-world properties. These networks are recursively constructed but retain a fixed, regular degree. They possess a unique one-dimensional lattice backbone overlaid by a hierarchical sequence of long-distance links, mixing real-space and small-world features. Both networks, one 3-regular and the other 4-regular, lead to distinct behaviors, as revealed by renormalization group studies. The 3-regular network is planar, has a diameter growing as √N with system size N, and leads to super-diffusion with an exact, anomalous exponent d w = 1.306..., but possesses only a trivial fixed point T c = 0 for the Ising ferromagnet. In turn, the 4-regular network is non-planar, has a diameter growing as ∼2 √(log 2 N 2 ) , exhibits 'ballistic' diffusion (d w = 1), and a non-trivial ferromagnetic transition, T c > 0. It suggests that the 3-regular network is still quite 'geometric', while the 4-regular network qualifies as a true small world with mean-field properties. As an engineering application we discuss synchronization of processors on these networks. (fast track communication)

  11. The hierarchical brain network for face recognition.

    Science.gov (United States)

    Zhen, Zonglei; Fang, Huizhen; Liu, Jia

    2013-01-01

    Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level.

  12. Discrete hierarchical organization of social group sizes.

    Science.gov (United States)

    Zhou, W-X; Sornette, D; Hill, R A; Dunbar, R I M

    2005-02-22

    The 'social brain hypothesis' for the evolution of large brains in primates has led to evidence for the coevolution of neocortical size and social group sizes, suggesting that there is a cognitive constraint on group size that depends, in some way, on the volume of neural material available for processing and synthesizing information on social relationships. More recently, work on both human and non-human primates has suggested that social groups are often hierarchically structured. We combine data on human grouping patterns in a comprehensive and systematic study. Using fractal analysis, we identify, with high statistical confidence, a discrete hierarchy of group sizes with a preferred scaling ratio close to three: rather than a single or a continuous spectrum of group sizes, humans spontaneously form groups of preferred sizes organized in a geometrical series approximating 3-5, 9-15, 30-45, etc. Such discrete scale invariance could be related to that identified in signatures of herding behaviour in financial markets and might reflect a hierarchical processing of social nearness by human brains.

  13. Hierarchical analysis of dependency in metabolic networks.

    Science.gov (United States)

    Gagneur, Julien; Jackson, David B; Casari, Georg

    2003-05-22

    Elucidation of metabolic networks for an increasing number of organisms reveals that even small networks can contain thousands of reactions and chemical species. The intimate connectivity between components complicates their decomposition into biologically meaningful sub-networks. Moreover, traditional higher-order representations of metabolic networks as metabolic pathways, suffers from the lack of rigorous definition, yielding pathways of disparate content and size. We introduce a hierarchical representation that emphasizes the gross organization of metabolic networks in largely independent pathways and sub-systems at several levels of independence. The approach highlights the coupling of different pathways and the shared compounds responsible for those couplings. By assessing our results on Escherichia coli (E.coli metabolic reactions, Genetic Circuits Research Group, University of California, San Diego, http://gcrg.ucsd.edu/organisms/ecoli.html, 'model v 1.01. reactions') against accepted biochemical annotations, we provide the first systematic synopsis of an organism's metabolism. Comparison with operons of E.coli shows that low-level clusters are reflected in genome organization and gene regulation. Source code, data sets and supplementary information are available at http://www.mas.ecp.fr/labo/equipe/gagneur/hierarchy/hierarchy.html

  14. Organization of excitable dynamics in hierarchical biological networks.

    Directory of Open Access Journals (Sweden)

    Mark Müller-Linow

    Full Text Available This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.

  15. Complex networks with scale-free nature and hierarchical modularity

    Science.gov (United States)

    Shekatkar, Snehal M.; Ambika, G.

    2015-09-01

    Generative mechanisms which lead to empirically observed structure of networked systems from diverse fields like biology, technology and social sciences form a very important part of study of complex networks. The structure of many networked systems like biological cell, human society and World Wide Web markedly deviate from that of completely random networks indicating the presence of underlying processes. Often the main process involved in their evolution is the addition of links between existing nodes having a common neighbor. In this context we introduce an important property of the nodes, which we call mediating capacity, that is generic to many networks. This capacity decreases rapidly with increase in degree, making hubs weak mediators of the process. We show that this property of nodes provides an explanation for the simultaneous occurrence of the observed scale-free structure and hierarchical modularity in many networked systems. This also explains the high clustering and small-path length seen in real networks as well as non-zero degree-correlations. Our study also provides insight into the local process which ultimately leads to emergence of preferential attachment and hence is also important in understanding robustness and control of real networks as well as processes happening on real networks.

  16. A Hierarchical Dispatch Structure for Distribution Network Pricing

    OpenAIRE

    Yuan, Zhao; Hesamzadeh, Mohammad Reza

    2015-01-01

    This paper presents a hierarchical dispatch structure for efficient distribution network pricing. The dispatch coordination problem in the context of hierarchical network operators are addressed. We formulate decentralized generation dispatch into a bilevel optimization problem in which main network operator and the connected distribution network operator optimize their costs in two levels. By using Karush-Kuhn-Tucker conditions and Fortuny-Amat McCarl linearization, the bilevel optimization ...

  17. Genomic analysis of the hierarchical structure of regulatory networks

    Science.gov (United States)

    Yu, Haiyuan; Gerstein, Mark

    2006-01-01

    A fundamental question in biology is how the cell uses transcription factors (TFs) to coordinate the expression of thousands of genes in response to various stimuli. The relationships between TFs and their target genes can be modeled in terms of directed regulatory networks. These relationships, in turn, can be readily compared with commonplace “chain-of-command” structures in social networks, which have characteristic hierarchical layouts. Here, we develop algorithms for identifying generalized hierarchies (allowing for various loop structures) and use these approaches to illuminate extensive pyramid-shaped hierarchical structures existing in the regulatory networks of representative prokaryotes (Escherichia coli) and eukaryotes (Saccharomyces cerevisiae), with most TFs at the bottom levels and only a few master TFs on top. These masters are situated near the center of the protein–protein interaction network, a different type of network from the regulatory one, and they receive most of the input for the whole regulatory hierarchy through protein interactions. Moreover, they have maximal influence over other genes, in terms of affecting expression-level changes. Surprisingly, however, TFs at the bottom of the regulatory hierarchy are more essential to the viability of the cell. Finally, one might think master TFs achieve their wide influence through directly regulating many targets, but TFs with most direct targets are in the middle of the hierarchy. We find, in fact, that these midlevel TFs are “control bottlenecks” in the hierarchy, and this great degree of control for “middle managers” has parallels in efficient social structures in various corporate and governmental settings. PMID:17003135

  18. GSMNet: A Hierarchical Graph Model for Moving Objects in Networks

    Directory of Open Access Journals (Sweden)

    Hengcai Zhang

    2017-03-01

    Full Text Available Existing data models for moving objects in networks are often limited by flexibly controlling the granularity of representing networks and the cost of location updates and do not encompass semantic information, such as traffic states, traffic restrictions and social relationships. In this paper, we aim to fill the gap of traditional network-constrained models and propose a hierarchical graph model called the Geo-Social-Moving model for moving objects in Networks (GSMNet that adopts four graph structures, RouteGraph, SegmentGraph, ObjectGraph and MoveGraph, to represent the underlying networks, trajectories and semantic information in an integrated manner. The bulk of user-defined data types and corresponding operators is proposed to handle moving objects and answer a new class of queries supporting three kinds of conditions: spatial, temporal and semantic information. Then, we develop a prototype system with the native graph database system Neo4Jto implement the proposed GSMNet model. In the experiment, we conduct the performance evaluation using simulated trajectories generated from the BerlinMOD (Berlin Moving Objects Database benchmark and compare with the mature MOD system Secondo. The results of 17 benchmark queries demonstrate that our proposed GSMNet model has strong potential to reduce time-consuming table join operations an d shows remarkable advantages with regard to representing semantic information and controlling the cost of location updates.

  19. Object recognition with hierarchical discriminant saliency networks

    Directory of Open Access Journals (Sweden)

    Sunhyoung eHan

    2014-09-01

    Full Text Available The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognitionmodel, the hierarchical discriminant saliency network (HDSN, whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. The HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a neuralnetwork implementation, all layers are convolutional and implement acombination of filtering, rectification, and pooling. The rectificationis performed with a parametric extension of the now popular rectified linearunits (ReLUs, whose parameters can be tuned for the detection of targetobject classes. This enables a number of functional enhancementsover neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation ofsaliency responses by the discriminant power of the underlying features,and the ability to detect both feature presence and absence.In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity totarget object classes and invariance. The resulting performance demonstrates benefits for all the functional enhancements of the HDSN.

  20. Object recognition with hierarchical discriminant saliency networks.

    Science.gov (United States)

    Han, Sunhyoung; Vasconcelos, Nuno

    2014-01-01

    The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

  1. Local Social Networks

    DEFF Research Database (Denmark)

    Sapuppo, Antonio; Sørensen, Lene Tolstrup

    2011-01-01

    Online social networks have become essential for many users in their daily communication. Through a combination of the online social networks with opportunistic networks, a new concept arises: Local Social Networks. The target of local social networks is to promote social networking benefits...... in physical environment in order to leverage personal affinities in the users' surroundings. The purpose of this paper is to present and discuss the concept of local social networks as a new social communication system. Particularly, the preliminary architecture and the prototype of local social networks...

  2. Multiple dynamical time-scales in networks with hierarchically

    Indian Academy of Sciences (India)

    Modular networks; hierarchical organization; synchronization. ... we show that such a topological structure gives rise to characteristic time-scale separation ... This suggests a possible functional role of such mesoscopic organization principle in ...

  3. Social entrepreneurship and social networks

    OpenAIRE

    Dufays, Frédéric

    2013-01-01

    In this presentation, we argue that the sociology of social networks may provide interesting insights with regard to the emergence of social entrepreneurship both at micro and macro levels. There have already been several calls for research on social networks in the context of social entrepreneurship (Certo & Miller 2008; Gedajlovic, et al. 2013; Haugh 2007; Mair & Marti 2006; Short, et al. 2009). These calls often address the differences in structure and effects of social networks in a socia...

  4. Road network safety evaluation using Bayesian hierarchical joint model.

    Science.gov (United States)

    Wang, Jie; Huang, Helai

    2016-05-01

    Safety and efficiency are commonly regarded as two significant performance indicators of transportation systems. In practice, road network planning has focused on road capacity and transport efficiency whereas the safety level of a road network has received little attention in the planning stage. This study develops a Bayesian hierarchical joint model for road network safety evaluation to help planners take traffic safety into account when planning a road network. The proposed model establishes relationships between road network risk and micro-level variables related to road entities and traffic volume, as well as socioeconomic, trip generation and network density variables at macro level which are generally used for long term transportation plans. In addition, network spatial correlation between intersections and their connected road segments is also considered in the model. A road network is elaborately selected in order to compare the proposed hierarchical joint model with a previous joint model and a negative binomial model. According to the results of the model comparison, the hierarchical joint model outperforms the joint model and negative binomial model in terms of the goodness-of-fit and predictive performance, which indicates the reasonableness of considering the hierarchical data structure in crash prediction and analysis. Moreover, both random effects at the TAZ level and the spatial correlation between intersections and their adjacent segments are found to be significant, supporting the employment of the hierarchical joint model as an alternative in road-network-level safety modeling as well. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Hierarchical Trust Management of COI in Heterogeneous Mobile Networks

    Science.gov (United States)

    2017-08-01

    Report: Hierarchical Trust Management of COI in Heterogeneous Mobile Networks The views, opinions and/or findings contained in this report are those of...Institute & State University Title: Hierarchical Trust Management of COI in Heterogeneous Mobile Networks Report Term: 0-Other Email: irchen@vt.edu...Reconfigurability, Survivability and Intrusion Tolerance for Community of Interest (COI) Applications – Our proposed COI trust management protocol will

  6. Cluster Based Hierarchical Routing Protocol for Wireless Sensor Network

    OpenAIRE

    Rashed, Md. Golam; Kabir, M. Hasnat; Rahim, Muhammad Sajjadur; Ullah, Shaikh Enayet

    2012-01-01

    The efficient use of energy source in a sensor node is most desirable criteria for prolong the life time of wireless sensor network. In this paper, we propose a two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol (CBHRP). We introduce a new concept called head-set, consists of one active cluster head and some other associate cluster heads within a cluster. The head-set members are responsible for control and management of the network. Results show that t...

  7. Multilevel compression of random walks on networks reveals hierarchical organization in large integrated systems.

    Directory of Open Access Journals (Sweden)

    Martin Rosvall

    Full Text Available To comprehend the hierarchical organization of large integrated systems, we introduce the hierarchical map equation, which reveals multilevel structures in networks. In this information-theoretic approach, we exploit the duality between compression and pattern detection; by compressing a description of a random walker as a proxy for real flow on a network, we find regularities in the network that induce this system-wide flow. Finding the shortest multilevel description of the random walker therefore gives us the best hierarchical clustering of the network--the optimal number of levels and modular partition at each level--with respect to the dynamics on the network. With a novel search algorithm, we extract and illustrate the rich multilevel organization of several large social and biological networks. For example, from the global air traffic network we uncover countries and continents, and from the pattern of scientific communication we reveal more than 100 scientific fields organized in four major disciplines: life sciences, physical sciences, ecology and earth sciences, and social sciences. In general, we find shallow hierarchical structures in globally interconnected systems, such as neural networks, and rich multilevel organizations in systems with highly separated regions, such as road networks.

  8. Road Network Selection Based on Road Hierarchical Structure Control

    Directory of Open Access Journals (Sweden)

    HE Haiwei

    2015-04-01

    Full Text Available A new road network selection method based on hierarchical structure is studied. Firstly, road network is built as strokes which are then classified into hierarchical collections according to the criteria of betweenness centrality value (BC value. Secondly, the hierarchical structure of the strokes is enhanced using structural characteristic identification technique. Thirdly, the importance calculation model was established according to the relationships among the hierarchical structure of the strokes. Finally, the importance values of strokes are got supported with the model's hierarchical calculation, and with which the road network is selected. Tests are done to verify the advantage of this method by comparing it with other common stroke-oriented methods using three kinds of typical road network data. Comparision of the results show that this method had few need to semantic data, and could eliminate the negative influence of edge strokes caused by the criteria of BC value well. So, it is better to maintain the global hierarchical structure of road network, and suitable to meet with the selection of various kinds of road network at the same time.

  9. Chimera states in networks of logistic maps with hierarchical connectivities

    Science.gov (United States)

    zur Bonsen, Alexander; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard

    2018-04-01

    Chimera states are complex spatiotemporal patterns consisting of coexisting domains of coherence and incoherence. We study networks of nonlocally coupled logistic maps and analyze systematically how the dilution of the network links influences the appearance of chimera patterns. The network connectivities are constructed using an iterative Cantor algorithm to generate fractal (hierarchical) connectivities. Increasing the hierarchical level of iteration, we compare the resulting spatiotemporal patterns. We demonstrate that a high clustering coefficient and symmetry of the base pattern promotes chimera states, and asymmetric connectivities result in complex nested chimera patterns.

  10. Detecting the overlapping and hierarchical community structure in complex networks

    International Nuclear Information System (INIS)

    Lancichinetti, Andrea; Fortunato, Santo; Kertesz, Janos

    2009-01-01

    Many networks in nature, society and technology are characterized by a mesoscopic level of organization, with groups of nodes forming tightly connected units, called communities or modules, that are only weakly linked to each other. Uncovering this community structure is one of the most important problems in the field of complex networks. Networks often show a hierarchical organization, with communities embedded within other communities; moreover, nodes can be shared between different communities. Here, we present the first algorithm that finds both overlapping communities and the hierarchical structure. The method is based on the local optimization of a fitness function. Community structure is revealed by peaks in the fitness histogram. The resolution can be tuned by a parameter enabling different hierarchical levels of organization to be investigated. Tests on real and artificial networks give excellent results.

  11. Diagnostic Classifiers: Revealing how Neural Networks Process Hierarchical Structure

    NARCIS (Netherlands)

    Veldhoen, S.; Hupkes, D.; Zuidema, W.

    2016-01-01

    We investigate how neural networks can be used for hierarchical, compositional semantics. To this end, we define the simple but nontrivial artificial task of processing nested arithmetic expressions and study whether different types of neural networks can learn to add and subtract. We find that

  12. A new hierarchical method to find community structure in networks

    Science.gov (United States)

    Saoud, Bilal; Moussaoui, Abdelouahab

    2018-04-01

    Community structure is very important to understand a network which represents a context. Many community detection methods have been proposed like hierarchical methods. In our study, we propose a new hierarchical method for community detection in networks based on genetic algorithm. In this method we use genetic algorithm to split a network into two networks which maximize the modularity. Each new network represents a cluster (community). Then we repeat the splitting process until we get one node at each cluster. We use the modularity function to measure the strength of the community structure found by our method, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our method are highly effective at discovering community structure in both computer-generated and real-world network data.

  13. Settings in Social Networks : a Measurement Model

    NARCIS (Netherlands)

    Schweinberger, Michael; Snijders, Tom A.B.

    2003-01-01

    A class of statistical models is proposed that aims to recover latent settings structures in social networks. Settings may be regarded as clusters of vertices. The measurement model is based on two assumptions. (1) The observed network is generated by hierarchically nested latent transitive

  14. Social network data analytics

    CERN Document Server

    Aggarwal, Charu C

    2011-01-01

    Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Pr

  15. Enterprise Social Networks

    DEFF Research Database (Denmark)

    Winkler, Till J.; Trier, Matthias

    2017-01-01

    Enterprise Social Networks (ESNs), d. h. Informationssysteme, die die Vernetzung von Mitarbeitern in Unternehmen fördern sollen, sind in verschiedenen Varianten und unter verschiedenen Bezeichnungen (etwa Enterprise Social Media, Corporate Social Software, Social Business oder Enterprise 2...

  16. Hierarchically structured distributed microprocessor network for control

    International Nuclear Information System (INIS)

    Greenwood, J.R.; Holloway, F.W.; Rupert, P.R.; Ozarski, R.G.; Suski, G.J.

    1979-01-01

    To satisfy a broad range of control-analysis and data-acquisition requirements for Shiva, a hierarchical, computer-based, modular-distributed control system was designed. This system handles the more than 3000 control elements and 1000 data acquisition units in a severe high-voltage, high-current environment. The control system design gives one a flexible and reliable configuration to meet the development milestones for Shiva within critical time limits

  17. Digital Social Network Mining for Topic Discovery

    Science.gov (United States)

    Moradianzadeh, Pooya; Mohi, Maryam; Sadighi Moshkenani, Mohsen

    Networked computers are expanding more and more around the world, and digital social networks becoming of great importance for many people's work and leisure. This paper mainly focused on discovering the topic of exchanging information in digital social network. In brief, our method is to use a hierarchical dictionary of related topics and words that mapped to a graph. Then, with comparing the extracted keywords from the context of social network with graph nodes, probability of relation between context and desired topics will be computed. This model can be used in many applications such as advertising, viral marketing and high-risk group detection.

  18. Hierarchical document categorization using associative networks

    NARCIS (Netherlands)

    Bloom, Niels; Theune, Mariet; de Jong, Franciska M.G.; Klement, E.P.; Borutzky, W.; Fahringer, T.; Hamza, M.H.; Uskov, V.

    Associative networks are a connectionist language model with the ability to handle dynamic data. We used two associative networks to categorize random sets of related Wikipedia articles with only their raw text as input. We then compared the resulting categorization to a gold standard: the manual

  19. Hierarchical organization of brain functional networks during visual tasks.

    Science.gov (United States)

    Zhuo, Zhao; Cai, Shi-Min; Fu, Zhong-Qian; Zhang, Jie

    2011-09-01

    The functional network of the brain is known to demonstrate modular structure over different hierarchical scales. In this paper, we systematically investigated the hierarchical modular organizations of the brain functional networks that are derived from the extent of phase synchronization among high-resolution EEG time series during a visual task. In particular, we compare the modular structure of the functional network from EEG channels with that of the anatomical parcellation of the brain cortex. Our results show that the modular architectures of brain functional networks correspond well to those from the anatomical structures over different levels of hierarchy. Most importantly, we find that the consistency between the modular structures of the functional network and the anatomical network becomes more pronounced in terms of vision, sensory, vision-temporal, motor cortices during the visual task, which implies that the strong modularity in these areas forms the functional basis for the visual task. The structure-function relationship further reveals that the phase synchronization of EEG time series in the same anatomical group is much stronger than that of EEG time series from different anatomical groups during the task and that the hierarchical organization of functional brain network may be a consequence of functional segmentation of the brain cortex.

  20. Changes of hierarchical network in local and world stock market

    Science.gov (United States)

    Patwary, Enayet Ullah; Lee, Jong Youl; Nobi, Ashadun; Kim, Doo Hwan; Lee, Jae Woo

    2017-10-01

    We consider the cross-correlation coefficients of the daily returns in the local and global stock markets. We generate the minimal spanning tree (MST) using the correlation matrix. We observe that the MSTs change their structure from chain-like networks to star-like networks during periods of market uncertainty. We quantify the measure of the hierarchical network utilizing the value of the hierarchy measured by the hierarchical path. The hierarchy and betweenness centrality characterize the state of the market regarding the impact of crises. During crises, the non-financial company is established as the central node of the MST. However, before the crisis and during stable periods, the financial company is occupying the central node of the MST in the Korean and the U.S. stock markets. The changes in the network structure and the central node are good indicators of an upcoming crisis.

  1. Interoperable Communications for Hierarchical Heterogeneous Wireless Networks

    Science.gov (United States)

    2016-04-01

    International Conference on Advanced Networks and Telecommuncations Systems (ANTS). 14-DEC-13, Kattankulathur, India. : , Husheng Li, Qi Zeng , Lijun Qian. GPS...correlation in space is too large, which implies that the correlation is overestimated. Other methods may be more accurate, faster or less memory ...limited, an intelligent mechanism is needed for the information selection and signaling design of the cross-network communication for collaborative

  2. Professional social networking.

    Science.gov (United States)

    Rowley, Robert D

    2014-12-01

    We review the current state of social communication between healthcare professionals, the role of consumer social networking, and some emerging technologies to address the gaps. In particular, the review covers (1) the current state of loose social networking for continuing medical education (CME) and other broadcast information dissemination; (2) social networking for business promotion; (3) social networking for peer collaboration, including simple communication as well as more robust data-centered collaboration around patient care; and (4) engaging patients on social platforms, including integrating consumer-originated data into the mix of healthcare data. We will see how, as the nature of healthcare delivery moves from the institution-centric way of tradition to a more social and networked ambulatory pattern that we see emerging today, the nature of health IT has also moved from enterprise-centric systems to more socially networked, cloud-based options.

  3. Next Generation Social Networks

    DEFF Research Database (Denmark)

    Sørensen, Lene Tolstrup; Skouby, Knud Erik

    2008-01-01

    different online networks for communities of people who share interests or individuals who presents themselves through user produced content is what makes up the social networking of today. The purpose of this paper is to discuss perceived user requirements to the next generation social networks. The paper...

  4. Hierarchical modeling of molecular energies using a deep neural network

    Science.gov (United States)

    Lubbers, Nicholas; Smith, Justin S.; Barros, Kipton

    2018-06-01

    We introduce the Hierarchically Interacting Particle Neural Network (HIP-NN) to model molecular properties from datasets of quantum calculations. Inspired by a many-body expansion, HIP-NN decomposes properties, such as energy, as a sum over hierarchical terms. These terms are generated from a neural network—a composition of many nonlinear transformations—acting on a representation of the molecule. HIP-NN achieves the state-of-the-art performance on a dataset of 131k ground state organic molecules and predicts energies with 0.26 kcal/mol mean absolute error. With minimal tuning, our model is also competitive on a dataset of molecular dynamics trajectories. In addition to enabling accurate energy predictions, the hierarchical structure of HIP-NN helps to identify regions of model uncertainty.

  5. Where sociality and relatedness diverge: the genetic basis for hierarchical social organization in African elephants

    DEFF Research Database (Denmark)

    Wittemyer, George; Okello, John B. A.; Rasmussen, Henrik B.

    2009-01-01

    Hierarchical properties characterize elephant fission-fusion social organization whereby stable groups of individuals coalesce into higher order groups or split in a predictable manner. This hierarchical complexity is rare among animals and, as such, an examination of the factors driving its......-tier level bonds, indicating the importance of direct benefits in the emergence of complex, hierarchical social relations among elephants. Future directions and conservation implications are discussed....

  6. Social cognitive radio networks

    CERN Document Server

    Chen, Xu

    2015-01-01

    This brief presents research results on social cognitive radio networks, a transformational and innovative networking paradigm that promotes the nexus between social interactions and cognitive radio networks. Along with a review of the research literature, the text examines the key motivation and challenges of social cognitive radio network design. Three socially inspired distributed spectrum sharing mechanisms are introduced: adaptive channel recommendation mechanism, imitation-based social spectrum sharing mechanism, and evolutionarily stable spectrum access mechanism. The brief concludes with a discussion of future research directions which ascertains that exploiting social interactions for distributed spectrum sharing will advance the state-of-the-art of cognitive radio network design, spur a new line of thinking for future wireless networks, and enable novel wireless service and applications.

  7. Metastable states in the hierarchical Dyson model drive parallel processing in the hierarchical Hopfield network

    International Nuclear Information System (INIS)

    Agliari, Elena; Barra, Adriano; Guerra, Francesco; Galluzzi, Andrea; Tantari, Daniele; Tavani, Flavia

    2015-01-01

    In this paper, we introduce and investigate the statistical mechanics of hierarchical neural networks. First, we approach these systems à la Mattis, by thinking of the Dyson model as a single-pattern hierarchical neural network. We also discuss the stability of different retrievable states as predicted by the related self-consistencies obtained both from a mean-field bound and from a bound that bypasses the mean-field limitation. The latter is worked out by properly reabsorbing the magnetization fluctuations related to higher levels of the hierarchy into effective fields for the lower levels. Remarkably, mixing Amit's ansatz technique for selecting candidate-retrievable states with the interpolation procedure for solving for the free energy of these states, we prove that, due to gauge symmetry, the Dyson model accomplishes both serial and parallel processing. We extend this scenario to multiple stored patterns by implementing the Hebb prescription for learning within the couplings. This results in Hopfield-like networks constrained on a hierarchical topology, for which, by restricting to the low-storage regime where the number of patterns grows at its most logarithmical with the amount of neurons, we prove the existence of the thermodynamic limit for the free energy, and we give an explicit expression of its mean-field bound and of its related improved bound. We studied the resulting self-consistencies for the Mattis magnetizations, which act as order parameters, are studied and the stability of solutions is analyzed to get a picture of the overall retrieval capabilities of the system according to both mean-field and non-mean-field scenarios. Our main finding is that embedding the Hebbian rule on a hierarchical topology allows the network to accomplish both serial and parallel processing. By tuning the level of fast noise affecting it or triggering the decay of the interactions with the distance among neurons, the system may switch from sequential retrieval to

  8. LSTM-Based Hierarchical Denoising Network for Android Malware Detection

    OpenAIRE

    Yan, Jinpei; Qi, Yong; Rao, Qifan

    2018-01-01

    Mobile security is an important issue on Android platform. Most malware detection methods based on machine learning models heavily rely on expert knowledge for manual feature engineering, which are still difficult to fully describe malwares. In this paper, we present LSTM-based hierarchical denoise network (HDN), a novel static Android malware detection method which uses LSTM to directly learn from the raw opcode sequences extracted from decompiled Android files. However, most opcode sequence...

  9. Hierarchical Communication Network Architectures for Offshore Wind Power Farms

    Directory of Open Access Journals (Sweden)

    Mohamed A. Ahmed

    2014-05-01

    Full Text Available Nowadays, large-scale wind power farms (WPFs bring new challenges for both electric systems and communication networks. Communication networks are an essential part of WPFs because they provide real-time control and monitoring of wind turbines from a remote location (local control center. However, different wind turbine applications have different requirements in terms of data volume, latency, bandwidth, QoS, etc. This paper proposes a hierarchical communication network architecture that consist of a turbine area network (TAN, farm area network (FAN, and control area network (CAN for offshore WPFs. The two types of offshore WPFs studied are small-scale WPFs close to the grid and medium-scale WPFs far from the grid. The wind turbines are modelled based on the logical nodes (LN concepts of the IEC 61400-25 standard. To keep pace with current developments in wind turbine technology, the network design takes into account the extension of the LNs for both the wind turbine foundation and meteorological measurements. The proposed hierarchical communication network is based on Switched Ethernet. Servers at the control center are used to store and process the data received from the WPF. The network architecture is modelled and evaluated via OPNET. We investigated the end-to-end (ETE delay for different WPF applications. The results are validated by comparing the amount of generated sensing data with that of received traffic at servers. The network performance is evaluated, analyzed and discussed in view of end-to-end (ETE delay for different link bandwidths.

  10. Multilayer Social Networks

    DEFF Research Database (Denmark)

    Dickison, Mark; Magnani, Matteo; Rossi, Luca

    social network systems, the evolution of interconnected social networks, and dynamic processes such as information spreading. A single real dataset is used to illustrate the concepts presented throughout the book, demonstrating both the practical utility and the potential shortcomings of the various...

  11. Social Networks and Health.

    Science.gov (United States)

    Perdiaris, Christos; Chardalias, Konstantinos; Magita, Andrianna; Mechili, Aggelos E; Diomidous, Marianna

    2015-01-01

    Nowadays the social networks have been developed into an advanced communications tool, which is important for all people to contact each other. These specific networks do offer lots of options as well as plenty of advantages and disadvantages. The social websites are many in number and titles, such as the facebook, the twitter, the bandoo etc. One of the most important function-mechanisms for the social network websites, are the marketing tools. The future goal is suggested to be the evolution of these programs. The development of these applications, which is going to lead into a new era for the social digital communication between the internet users, all around the globe.

  12. Hierarchical-control-based output synchronization of coexisting attractor networks

    International Nuclear Information System (INIS)

    Yun-Zhong, Song; Yi-Fa, Tang

    2010-01-01

    This paper introduces the concept of hierarchical-control-based output synchronization of coexisting attractor networks. Within the new framework, each dynamic node is made passive at first utilizing intra-control around its own arena. Then each dynamic node is viewed as one agent, and on account of that, the solution of output synchronization of coexisting attractor networks is transformed into a multi-agent consensus problem, which is made possible by virtue of local interaction between individual neighbours; this distributed working way of coordination is coined as inter-control, which is only specified by the topological structure of the network. Provided that the network is connected and balanced, the output synchronization would come true naturally via synergy between intra and inter-control actions, where the Tightness is proved theoretically via convex composite Lyapunov functions. For completeness, several illustrative examples are presented to further elucidate the novelty and efficacy of the proposed scheme. (general)

  13. Growth and containment of a hierarchical criminal network

    Science.gov (United States)

    Marshak, Charles Z.; Rombach, M. Puck; Bertozzi, Andrea L.; D'Orsogna, Maria R.

    2016-02-01

    We model the hierarchical evolution of an organized criminal network via antagonistic recruitment and pursuit processes. Within the recruitment phase, a criminal kingpin enlists new members into the network, who in turn seek out other affiliates. New recruits are linked to established criminals according to a probability distribution that depends on the current network structure. At the same time, law enforcement agents attempt to dismantle the growing organization using pursuit strategies that initiate on the lower level nodes and that unfold as self-avoiding random walks. The global details of the organization are unknown to law enforcement, who must explore the hierarchy node by node. We halt the pursuit when certain local criteria of the network are uncovered, encoding if and when an arrest is made; the criminal network is assumed to be eradicated if the kingpin is arrested. We first analyze recruitment and study the large scale properties of the growing network; later we add pursuit and use numerical simulations to study the eradication probability in the case of three pursuit strategies, the time to first eradication, and related costs. Within the context of this model, we find that eradication becomes increasingly costly as the network increases in size and that the optimal way of arresting the kingpin is to intervene at the early stages of network formation. We discuss our results in the context of dark network disruption and their implications on possible law enforcement strategies.

  14. Computational Social Network Analysis

    CERN Document Server

    Hassanien, Aboul-Ella

    2010-01-01

    Presents insight into the social behaviour of animals (including the study of animal tracks and learning by members of the same species). This book provides web-based evidence of social interaction, perceptual learning, information granulation and the behaviour of humans and affinities between web-based social networks

  15. Hierarchical modular granular neural networks with fuzzy aggregation

    CERN Document Server

    Sanchez, Daniela

    2016-01-01

    In this book, a new method for hybrid intelligent systems is proposed. The proposed method is based on a granular computing approach applied in two levels. The techniques used and combined in the proposed method are modular neural networks (MNNs) with a Granular Computing (GrC) approach, thus resulting in a new concept of MNNs; modular granular neural networks (MGNNs). In addition fuzzy logic (FL) and hierarchical genetic algorithms (HGAs) are techniques used in this research work to improve results. These techniques are chosen because in other works have demonstrated to be a good option, and in the case of MNNs and HGAs, these techniques allow to improve the results obtained than with their conventional versions; respectively artificial neural networks and genetic algorithms.

  16. PERSON IN SOCIAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Андрей Борисович Шалимов

    2013-11-01

    Full Text Available Purpose: Our scientific purpose is creation of practical model of person’s representation in social networks (Facebook, Twitter, Classmates. As user of social networks, person is made conditional not only upon its own identity, but also upon the information about himself, which he is ready to share with his friends in contact list. Goal-setting and practical activities for their achievement mean that you should apply force, it can completely eliminates systemic factors, the system of power relations, which overwhelms human being in social networks.Methodology: The reconstruction of the model of human in the popularity of social networksResults: There is descripton of practical model of person's representation in social networks, it includes the management of own identity and the audience (the list of contacts. When person manages own identity, he answers the question, «Whom I can dare to be?». Person perceives himself in social networks' being, he understands himself and his place in the world, he identifies.Managing the way in social media means that you answer the question «What I want to tell?». Person in social media looks at events in the field of culture, economy, politics, social relations through the prism of his own attitudes, he forms and formulates his own agenda and he is going to tell about himself through them.Practical implications: Everyday people’s life, practical activities, including marketing in social networks.DOI: http://dx.doi.org/10.12731/2218-7405-2013-9-51

  17. Social Networks and the Environment

    OpenAIRE

    Julio Videras

    2013-01-01

    This review discusses empirical research on social networks and the environment; it summarizes findings from representative studies and the conceptual frameworks social scientists use to examine the role of social networks. The article presents basic concepts in social network analysis, summarizes common challenges of empirical research on social networks, and outlines areas for future research. Finally, the article discusses the normative and positive meanings of social networks.

  18. Hierarchical prediction errors in midbrain and septum during social learning.

    Science.gov (United States)

    Diaconescu, Andreea O; Mathys, Christoph; Weber, Lilian A E; Kasper, Lars; Mauer, Jan; Stephan, Klaas E

    2017-04-01

    Social learning is fundamental to human interactions, yet its computational and physiological mechanisms are not well understood. One prominent open question concerns the role of neuromodulatory transmitters. We combined fMRI, computational modelling and genetics to address this question in two separate samples (N = 35, N = 47). Participants played a game requiring inference on an adviser's intentions whose motivation to help or mislead changed over time. Our analyses suggest that hierarchically structured belief updates about current advice validity and the adviser's trustworthiness, respectively, depend on different neuromodulatory systems. Low-level prediction errors (PEs) about advice accuracy not only activated regions known to support 'theory of mind', but also the dopaminergic midbrain. Furthermore, PE responses in ventral striatum were influenced by the Met/Val polymorphism of the Catechol-O-Methyltransferase (COMT) gene. By contrast, high-level PEs ('expected uncertainty') about the adviser's fidelity activated the cholinergic septum. These findings, replicated in both samples, have important implications: They suggest that social learning rests on hierarchically related PEs encoded by midbrain and septum activity, respectively, in the same manner as other forms of learning under volatility. Furthermore, these hierarchical PEs may be broadcast by dopaminergic and cholinergic projections to induce plasticity specifically in cortical areas known to represent beliefs about others. © The Author (2017). Published by Oxford University Press.

  19. [Social networks and medicine].

    Science.gov (United States)

    Bastardot, F; Vollenweider, P; Marques-Vidal, P

    2015-11-04

    Social networks (social media or #SoMe) have entered medical practice within the last few years. These new media--like Twitter or Skype--enrich interactions among physicians (telemedicine), among physicians and patients (virtual consultations) and change the way of teaching medicine. They also entail new ethical, deontological and legal issues: the extension of the consultation area beyond the medical office and the access of information by third parties were recently debated. We develop here a review of some social networks with their characteristics, applications for medicine and limitations, and we offer some recommendations of good practice.

  20. Complex networks as an emerging property of hierarchical preferential attachment

    Science.gov (United States)

    Hébert-Dufresne, Laurent; Laurence, Edward; Allard, Antoine; Young, Jean-Gabriel; Dubé, Louis J.

    2015-12-01

    Real complex systems are not rigidly structured; no clear rules or blueprints exist for their construction. Yet, amidst their apparent randomness, complex structural properties universally emerge. We propose that an important class of complex systems can be modeled as an organization of many embedded levels (potentially infinite in number), all of them following the same universal growth principle known as preferential attachment. We give examples of such hierarchy in real systems, for instance, in the pyramid of production entities of the film industry. More importantly, we show how real complex networks can be interpreted as a projection of our model, from which their scale independence, their clustering, their hierarchy, their fractality, and their navigability naturally emerge. Our results suggest that complex networks, viewed as growing systems, can be quite simple, and that the apparent complexity of their structure is largely a reflection of their unobserved hierarchical nature.

  1. Visual question answering using hierarchical dynamic memory networks

    Science.gov (United States)

    Shang, Jiayu; Li, Shiren; Duan, Zhikui; Huang, Junwei

    2018-04-01

    Visual Question Answering (VQA) is one of the most popular research fields in machine learning which aims to let the computer learn to answer natural language questions with images. In this paper, we propose a new method called hierarchical dynamic memory networks (HDMN), which takes both question attention and visual attention into consideration impressed by Co-Attention method, which is the best (or among the best) algorithm for now. Additionally, we use bi-directional LSTMs, which have a better capability to remain more information from the question and image, to replace the old unit so that we can capture information from both past and future sentences to be used. Then we rebuild the hierarchical architecture for not only question attention but also visual attention. What's more, we accelerate the algorithm via a new technic called Batch Normalization which helps the network converge more quickly than other algorithms. The experimental result shows that our model improves the state of the art on the large COCO-QA dataset, compared with other methods.

  2. Online social support networks.

    Science.gov (United States)

    Mehta, Neil; Atreja, Ashish

    2015-04-01

    Peer support groups have a long history and have been shown to improve health outcomes. With the increasing familiarity with online social networks like Facebook and ubiquitous access to the Internet, online social support networks are becoming popular. While studies have shown the benefit of these networks in providing emotional support or meeting informational needs, robust data on improving outcomes such as a decrease in health services utilization or reduction in adverse outcomes is lacking. These networks also pose unique challenges in the areas of patient privacy, funding models, quality of content, and research agendas. Addressing these concerns while creating patient-centred, patient-powered online support networks will help leverage these platforms to complement traditional healthcare delivery models in the current environment of value-based care.

  3. Social exchange: Relations and networks

    OpenAIRE

    Dijkstra, Jacob

    2015-01-01

    In this short paper, I review the literature on social exchange networks, with specific attention to theoretical and experimental research. I indicate how social exchange theory is rooted in general social theory and mention a few of its main links to social network analysis and empirical network research. The paper provides an accessible entry into the literature on social exchange.

  4. Privacy in social networking sites

    OpenAIRE

    Λεονάρδος, Γεώργιος; Leonardos, Giorgos

    2016-01-01

    The purpose of this study is to explore the aspects of privacy over the use of social networks web sites. More specific, we will show the types of social networks, their privacy mechanisms that are different in each social network site, their privacy options that are offered to users. We will report some serious privacy violations incidents of the most popular social networks sites such as Facebook, Twitter, LinkedIn. Also, we will report some important surveys about social networks and pr...

  5. Online Advertising in Social Networks

    Science.gov (United States)

    Bagherjeiran, Abraham; Bhatt, Rushi P.; Parekh, Rajesh; Chaoji, Vineet

    Online social networks offer opportunities to analyze user behavior and social connectivity and leverage resulting insights for effective online advertising. This chapter focuses on the role of social network information in online display advertising.

  6. Philosophy of social networking

    Directory of Open Access Journals (Sweden)

    Markova T. V.

    2018-04-01

    Full Text Available the article is devoted to the study of social networks impact on an individual, which are an important part of a modern society. Through reflections the reasons of the popularity of the phenomenon of virtual communication in the 21st century are determined: what drives a person when he / she registers on the sites for communication, premises for his / her actions and consequences. The latter is viewed from both a social and a personal point of view. After analyzing the charts of social networks popularity, the authors come to the conclusion that there is an increase in the population of the virtual communication supporters. It allows to assert that the problem of the termination of live communication is relevant to this day. Dualism of social networks influence on the consciousness of an individual is stated: together with negative consequences positive aspects are considered. By analyzing social media researches, as well as by the means of a survey, the dominant reason for the world wide web entering is identified. After that, it is clearly shown what a typical site for communication is; as a result, the pros and cons of such time spending are specified. The conclusion states the predominance of the Internet dependence over the other types of dependencies, also forecasts are made for the future of both social networks and the people caught in their web.

  7. A hierarchical network modeling method for railway tunnels safety assessment

    Science.gov (United States)

    Zhou, Jin; Xu, Weixiang; Guo, Xin; Liu, Xumin

    2017-02-01

    Using network theory to model risk-related knowledge on accidents is regarded as potential very helpful in risk management. A large amount of defects detection data for railway tunnels is collected in autumn every year in China. It is extremely important to discover the regularities knowledge in database. In this paper, based on network theories and by using data mining techniques, a new method is proposed for mining risk-related regularities to support risk management in railway tunnel projects. A hierarchical network (HN) model which takes into account the tunnel structures, tunnel defects, potential failures and accidents is established. An improved Apriori algorithm is designed to rapidly and effectively mine correlations between tunnel structures and tunnel defects. Then an algorithm is presented in order to mine the risk-related regularities table (RRT) from the frequent patterns. At last, a safety assessment method is proposed by consideration of actual defects and possible risks of defects gained from the RRT. This method cannot only generate the quantitative risk results but also reveal the key defects and critical risks of defects. This paper is further development on accident causation network modeling methods which can provide guidance for specific maintenance measure.

  8. Hierarchical feedback modules and reaction hubs in cell signaling networks.

    Science.gov (United States)

    Xu, Jianfeng; Lan, Yueheng

    2015-01-01

    Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks.

  9. Hierarchical feedback modules and reaction hubs in cell signaling networks.

    Directory of Open Access Journals (Sweden)

    Jianfeng Xu

    Full Text Available Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks.

  10. Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

    Science.gov (United States)

    Xu, Jianfeng; Lan, Yueheng

    2015-01-01

    Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347

  11. The Social Network Classroom

    Science.gov (United States)

    Bunus, Peter

    Online social networking is an important part in the everyday life of college students. Despite the increasing popularity of online social networking among students and faculty members, its educational benefits are largely untested. This paper presents our experience in using social networking applications and video content distribution websites as a complement of traditional classroom education. In particular, the solution has been based on effective adaptation, extension and integration of Facebook, Twitter, Blogger YouTube and iTunes services for delivering educational material to students on mobile platforms like iPods and 3 rd generation mobile phones. The goals of the proposed educational platform, described in this paper, are to make the learning experience more engaging, to encourage collaborative work and knowledge sharing among students, and to provide an interactive platform for the educators to reach students and deliver lecture material in a totally new way.

  12. Dynamic social networks based on movement

    Science.gov (United States)

    Scharf, Henry; Hooten, Mevin B.; Fosdick, Bailey K.; Johnson, Devin S.; London, Joshua M.; Durban, John W.

    2016-01-01

    Network modeling techniques provide a means for quantifying social structure in populations of individuals. Data used to define social connectivity are often expensive to collect and based on case-specific, ad hoc criteria. Moreover, in applications involving animal social networks, collection of these data is often opportunistic and can be invasive. Frequently, the social network of interest for a given population is closely related to the way individuals move. Thus, telemetry data, which are minimally invasive and relatively inexpensive to collect, present an alternative source of information. We develop a framework for using telemetry data to infer social relationships among animals. To achieve this, we propose a Bayesian hierarchical model with an underlying dynamic social network controlling movement of individuals via two mechanisms: an attractive effect and an aligning effect. We demonstrate the model and its ability to accurately identify complex social behavior in simulation, and apply our model to telemetry data arising from killer whales. Using auxiliary information about the study population, we investigate model validity and find the inferred dynamic social network is consistent with killer whale ecology and expert knowledge.

  13. LSTM-Based Hierarchical Denoising Network for Android Malware Detection

    Directory of Open Access Journals (Sweden)

    Jinpei Yan

    2018-01-01

    Full Text Available Mobile security is an important issue on Android platform. Most malware detection methods based on machine learning models heavily rely on expert knowledge for manual feature engineering, which are still difficult to fully describe malwares. In this paper, we present LSTM-based hierarchical denoise network (HDN, a novel static Android malware detection method which uses LSTM to directly learn from the raw opcode sequences extracted from decompiled Android files. However, most opcode sequences are too long for LSTM to train due to the gradient vanishing problem. Hence, HDN uses a hierarchical structure, whose first-level LSTM parallelly computes on opcode subsequences (we called them method blocks to learn the dense representations; then the second-level LSTM can learn and detect malware through method block sequences. Considering that malicious behavior only appears in partial sequence segments, HDN uses method block denoise module (MBDM for data denoising by adaptive gradient scaling strategy based on loss cache. We evaluate and compare HDN with the latest mainstream researches on three datasets. The results show that HDN outperforms these Android malware detection methods,and it is able to capture longer sequence features and has better detection efficiency than N-gram-based malware detection which is similar to our method.

  14. Impact of hierarchical modular structure on ranking of individual nodes in directed networks

    Energy Technology Data Exchange (ETDEWEB)

    Masuda, Naoki [Graduate School of Information Science and Technology, University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo 113-8656 (Japan); Kawamura, Yoji [Institute for Research on Earth Evolution, Japan Agency for Marine-Earth Science and Technology, 3173-25 Showa-machi, Kanazawa-ku, Yokohama, Kanagawa 236-0001 (Japan); Kori, Hiroshi [PRESTO, Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan)], E-mail: masuda@mist.i.u-tokyo.ac.jp

    2009-11-15

    Many systems, ranging from biological and engineering systems to social systems, can be modeled as directed networks, with links representing directed interaction between two nodes. To assess the importance of a node in a directed network, various centrality measures based on different criteria have been proposed. However, calculating the centrality of a node is often difficult because of the overwhelming size of the network or because the information held about the network is incomplete. Thus, developing an approximation method for estimating centrality measures is needed. In this study, we focus on modular networks; many real-world networks are composed of modules, where connection is dense within a module and sparse across different modules. We show that ranking-type centrality measures, including the PageRank, can be efficiently estimated once the modular structure of a network is extracted. We develop an analytical method to evaluate the centrality of nodes by combining the local property (i.e. indegree and outdegree of nodes) and the global property (i.e. centrality of modules). The proposed method is corroborated by real data. Our results provide a linkage between the ranking-type centrality values of modules and those of individual nodes. They also reveal the hierarchical structure of networks in the sense of subordination (not nestedness) laid out by connectivity among modules of different relative importance. The present study raises a novel motive for identifying modules in networks.

  15. Impact of hierarchical modular structure on ranking of individual nodes in directed networks

    International Nuclear Information System (INIS)

    Masuda, Naoki; Kawamura, Yoji; Kori, Hiroshi

    2009-01-01

    Many systems, ranging from biological and engineering systems to social systems, can be modeled as directed networks, with links representing directed interaction between two nodes. To assess the importance of a node in a directed network, various centrality measures based on different criteria have been proposed. However, calculating the centrality of a node is often difficult because of the overwhelming size of the network or because the information held about the network is incomplete. Thus, developing an approximation method for estimating centrality measures is needed. In this study, we focus on modular networks; many real-world networks are composed of modules, where connection is dense within a module and sparse across different modules. We show that ranking-type centrality measures, including the PageRank, can be efficiently estimated once the modular structure of a network is extracted. We develop an analytical method to evaluate the centrality of nodes by combining the local property (i.e. indegree and outdegree of nodes) and the global property (i.e. centrality of modules). The proposed method is corroborated by real data. Our results provide a linkage between the ranking-type centrality values of modules and those of individual nodes. They also reveal the hierarchical structure of networks in the sense of subordination (not nestedness) laid out by connectivity among modules of different relative importance. The present study raises a novel motive for identifying modules in networks.

  16. Social exchange : Relations and networks

    NARCIS (Netherlands)

    Dijkstra, Jacob

    2015-01-01

    In this short paper, I review the literature on social exchange networks, with specific attention to theoretical and experimental research. I indicate how social exchange theory is rooted in general social theory and mention a few of its main links to social network analysis and empirical network

  17. Communication in Animal Social Networks

    NARCIS (Netherlands)

    Snijders, Lysanne; Naguib, Marc

    2017-01-01

    Animal social networks and animal communication networks are key disciplines for understanding animal social behavior, yet these disciplines remain poorly integrated. In this review, we show how communication and social networks are inherently linked, with social signals reflecting and affecting

  18. Power to Detect Intervention Effects on Ensembles of Social Networks

    Science.gov (United States)

    Sweet, Tracy M.; Junker, Brian W.

    2016-01-01

    The hierarchical network model (HNM) is a framework introduced by Sweet, Thomas, and Junker for modeling interventions and other covariate effects on ensembles of social networks, such as what would be found in randomized controlled trials in education research. In this article, we develop calculations for the power to detect an intervention…

  19. Social network and addiction.

    Science.gov (United States)

    La Barbera, Daniele; La Paglia, Filippo; Valsavoia, Rosaria

    2009-01-01

    In recent decades, the rapid development of innovative Internet-based communication technologies created a new field of academic study among scholars. Particularly, the attention of researchers is focusing on new ways to form relationship-thought social web. Social Network sites constitute a new form of web communities, where people meet and share interests and activities. Due to exponential growth of these sites, an increasing number of scholars are beginning to study the emergent phenomena in order to identify any psychopathological risk related to use of social web, such as addiction. This article examines the recent literature about this issue.

  20. PSN: Portfolio Social Network

    DEFF Research Database (Denmark)

    Cortes, Jordi Magrina; Nizamani, Sarwat; Memon, Nasrullah

    2014-01-01

    In this paper we present a web-based information system which is a portfolio social network (PSN) that provides solutions to the recruiters and job seekers. The proposed system enables users to create portfolio so that he/she can add his specializations with piece of code if any specifically...

  1. Foraging Online Social Networks

    NARCIS (Netherlands)

    Koot, G.; Huis in ’t Veld, M.A.A.; Hendricksen, J.; Vries, A. de; Broek, E.L. van den

    2014-01-01

    A concise and practical introduction is given on Online Social Networks (OSN) and their application in law enforcement, including a brief survey of related work. Subsequently, a tool is introduced that can be used to search OSN in order to generate user profiles. Both its architecture and processing

  2. Change Detection in Social Networks

    National Research Council Canada - National Science Library

    McCulloh, Ian; Webb, Matthew; Graham, John; Carley, Kathleen; Horn, Daniel B

    2008-01-01

    .... This project proposes a new method for detecting change in social networks over time, by applying a cumulative sum statistical process control statistic to normally distributed network measures...

  3. Online Social Network Interactions:

    Directory of Open Access Journals (Sweden)

    Hui-Jung Chang

    2018-01-01

    Full Text Available A cross-cultural comparison of social networking structure on McDonald’s Facebook fan sites between Taiwan and the USA was conducted utilizing the individualism/collectivism dimension proposed by Hofstede. Four network indicators are used to describe the network structure of McDonald’s Facebook fan sites: size, density, clique and centralization. Individuals who post on both Facebook sites for the year of 2012 were considered as network participants for the purpose of the study. Due to the huge amount of data, only one thread of postings was sampled from each month of the year of 2012. The final data consists of 1002 postings written by 896 individuals and 5962 postings written by 5532 individuals from Taiwan and the USA respectively. The results indicated that the USA McDonald’s Facebook fan network has more fans, while Taiwan’s McDonald’s Facebook fan network is more densely connected. Cliques did form among the overall multiplex and within the individual uniplex networks in two countries, yet no significant differences were found between them. All the fan networks in both countries are relatively centralized, mostly on the site operators.

  4. Promoting Social Network Awareness: A Social Network Monitoring System

    Science.gov (United States)

    Cadima, Rita; Ferreira, Carlos; Monguet, Josep; Ojeda, Jordi; Fernandez, Joaquin

    2010-01-01

    To increase communication and collaboration opportunities, members of a community must be aware of the social networks that exist within that community. This paper describes a social network monitoring system--the KIWI system--that enables users to register their interactions and visualize their social networks. The system was implemented in a…

  5. Multiple simultaneous fault diagnosis via hierarchical and single artificial neural networks

    International Nuclear Information System (INIS)

    Eslamloueyan, R.; Shahrokhi, M.; Bozorgmehri, R.

    2003-01-01

    Process fault diagnosis involves interpreting the current status of the plant given sensor reading and process knowledge. There has been considerable work done in this area with a variety of approaches being proposed for process fault diagnosis. Neural networks have been used to solve process fault diagnosis problems in chemical process, as they are well suited for recognizing multi-dimensional nonlinear patterns. In this work, the use of Hierarchical Artificial Neural Networks in diagnosing the multi-faults of a chemical process are discussed and compared with that of Single Artificial Neural Networks. The lower efficiency of Hierarchical Artificial Neural Networks , in comparison to Single Artificial Neural Networks, in process fault diagnosis is elaborated and analyzed. Also, the concept of a multi-level selection switch is presented and developed to improve the performance of hierarchical artificial neural networks. Simulation results indicate that application of multi-level selection switch increase the performance of the hierarchical artificial neural networks considerably

  6. Hierarchical Data Distribution Scheme for Peer-to-Peer Networks

    Science.gov (United States)

    Bhushan, Shashi; Dave, M.; Patel, R. B.

    2010-11-01

    In the past few years, peer-to-peer (P2P) networks have become an extremely popular mechanism for large-scale content sharing. P2P systems have focused on specific application domains (e.g. music files, video files) or on providing file system like capabilities. P2P is a powerful paradigm, which provides a large-scale and cost-effective mechanism for data sharing. P2P system may be used for storing data globally. Can we implement a conventional database on P2P system? But successful implementation of conventional databases on the P2P systems is yet to be reported. In this paper we have presented the mathematical model for the replication of the partitions and presented a hierarchical based data distribution scheme for the P2P networks. We have also analyzed the resource utilization and throughput of the P2P system with respect to the availability, when a conventional database is implemented over the P2P system with variable query rate. Simulation results show that database partitions placed on the peers with higher availability factor perform better. Degradation index, throughput, resource utilization are the parameters evaluated with respect to the availability factor.

  7. Individual Search and Social Networks

    OpenAIRE

    Sanjeev Goyal; Stephanie Rosenkranz; Utz Weitzel; Vincent Buskens

    2014-01-01

    The explosion in online social networks motivates an enquiry into their structure and their welfare effects. A central feature of these networks is information sharing: online social networks lower the cost of getting information from others. These lower costs affect the attractiveness of individual search vis-a-vis a reliance on social networks. The paper reports the findings of an experiment on these effects. Our experiment shows that online networks can have large effects. Information acqu...

  8. A Comparison of Online Social Networks and Real-Life Social Networks: A Study of Sina Microblogging

    Directory of Open Access Journals (Sweden)

    Dayong Zhang

    2014-01-01

    Full Text Available Online social networks appear to enrich our social life, which raises the question whether they remove cognitive constraints on human communication and improve human social capabilities. In this paper, we analyze the users' following and followed relationships based on the data of Sina Microblogging and reveal several structural properties of Sina Microblogging. Compared with real-life social networks, our results confirm some similar features. However, Sina Microblogging also shows its own specialties, such as hierarchical structure and degree disassortativity, which all mark a deviation from real-life social networks. The low cost of the online network forms a broader perspective, and the one-way link relationships make it easy to spread information, but the online social network does not make too much difference in the creation of strong interpersonal relationships. Finally, we describe the mechanisms for the formation of these characteristics and discuss the implications of these structural properties for the real-life social networks.

  9. The moderating role of attachment anxiety on social network site use intensity and social capital.

    Science.gov (United States)

    Liu, Haihua; Shi, Junqi; Liu, Yihao; Sheng, Zitong

    2013-02-01

    This study examined the moderating role of attachment anxiety on the relationship between intensity of social network site use and bridging, bonding, and maintained social capital. Data from 322 undergraduate Chinese students were collected. Hierarchical regression analyses showed positive relationships between online intensity of social network site use and the three types of social capital. Moreover, attachment anxiety moderated the effect of intensity of social network site use on social capital. Specifically, for students with lower attachment anxiety, the relationships between intensity of social network site use and bonding and bridging social capital were stronger than those with higher attachment anxiety. The result suggested that social network sites cannot improve highly anxiously attached individuals' social capital effectively; they may need more face-to-face communications.

  10. Transition and Social networks

    OpenAIRE

    Raghavan, Raghu; Pawson, N.

    2011-01-01

    School leavers with learning disabilities often face difficulties in making a smooth transition from school to college, employment or more broadly, to adult life. The transition phase is traumatic for the young person with learning disabilities and their families as it often results in the loss of friendships, relationships and social networks. The aim of this chapter is to explore the issues of transition from adolescence to adulthood for young people with learning disabilities and its effe...

  11. Resolution of Singularities Introduced by Hierarchical Structure in Deep Neural Networks.

    Science.gov (United States)

    Nitta, Tohru

    2017-10-01

    We present a theoretical analysis of singular points of artificial deep neural networks, resulting in providing deep neural network models having no critical points introduced by a hierarchical structure. It is considered that such deep neural network models have good nature for gradient-based optimization. First, we show that there exist a large number of critical points introduced by a hierarchical structure in deep neural networks as straight lines, depending on the number of hidden layers and the number of hidden neurons. Second, we derive a sufficient condition for deep neural networks having no critical points introduced by a hierarchical structure, which can be applied to general deep neural networks. It is also shown that the existence of critical points introduced by a hierarchical structure is determined by the rank and the regularity of weight matrices for a specific class of deep neural networks. Finally, two kinds of implementation methods of the sufficient conditions to have no critical points are provided. One is a learning algorithm that can avoid critical points introduced by the hierarchical structure during learning (called avoidant learning algorithm). The other is a neural network that does not have some critical points introduced by the hierarchical structure as an inherent property (called avoidant neural network).

  12. Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization

    Directory of Open Access Journals (Sweden)

    Lianbo Ma

    2014-01-01

    Full Text Available This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

  13. A Hierarchical Convolutional Neural Network for vesicle fusion event classification.

    Science.gov (United States)

    Li, Haohan; Mao, Yunxiang; Yin, Zhaozheng; Xu, Yingke

    2017-09-01

    Quantitative analysis of vesicle exocytosis and classification of different modes of vesicle fusion from the fluorescence microscopy are of primary importance for biomedical researches. In this paper, we propose a novel Hierarchical Convolutional Neural Network (HCNN) method to automatically identify vesicle fusion events in time-lapse Total Internal Reflection Fluorescence Microscopy (TIRFM) image sequences. Firstly, a detection and tracking method is developed to extract image patch sequences containing potential fusion events. Then, a Gaussian Mixture Model (GMM) is applied on each image patch of the patch sequence with outliers rejected for robust Gaussian fitting. By utilizing the high-level time-series intensity change features introduced by GMM and the visual appearance features embedded in some key moments of the fusion process, the proposed HCNN architecture is able to classify each candidate patch sequence into three classes: full fusion event, partial fusion event and non-fusion event. Finally, we validate the performance of our method on 9 challenging datasets that have been annotated by cell biologists, and our method achieves better performances when comparing with three previous methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Hierarchical artificial bee colony algorithm for RFID network planning optimization.

    Science.gov (United States)

    Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

    2014-01-01

    This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

  15. A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

    DEFF Research Database (Denmark)

    Ding, Tao; Li, Cheng; Huang, Can

    2018-01-01

    –slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost......In order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master...... optimality. Numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods....

  16. Hierarchical anatomical brain networks for MCI prediction: revisiting volumetric measures.

    Directory of Open Access Journals (Sweden)

    Luping Zhou

    results. Without requiring new sources of information, our proposed approach improves the accuracy of MCI prediction from 80.83% (of conventional volumetric features to 84.35% (of hierarchical network features, evaluated using data sets randomly drawn from the ADNI (Alzheimer's Disease Neuroimaging Initiative dataset.

  17. Social Networking Sites in Education

    OpenAIRE

    Suková, Lenka

    2010-01-01

    Diploma thesis deals with social networking sites and their use in education. Thesis is divided into two general parts. The first part deals with theory of learning; Bloom's taxonomy of educational objectives and new educational theory based on learning in networks -- Connectivism. After that thesis focuses on the definition of social networking sites, introduction of some of the best known social networking sites and examples of their use in foreign and domestic educational practice. The sec...

  18. Conceptualizing of Social Networking Sites

    OpenAIRE

    J. S. Sodhi; Shilpi Sharma

    2012-01-01

    People often move to their friends, families and colleagues when they feel urge and having doubts or queries to solve. Participation in social networking site has dramatically increased in recent years. Many social networking sites boost with million of members using their network on regular basis to communicate, share , create and collaborate with others. In this paper we explore the phenomenon of using social networking site to trace a link of the search from the community of users for bett...

  19. Signed Networks in Social Media

    OpenAIRE

    Leskovec, Jure; Huttenlocher, Daniel; Kleinberg, Jon

    2010-01-01

    Relations between users on social media sites often reflect a mixture of positive (friendly) and negative (antagonistic) interactions. In contrast to the bulk of research on social networks that has focused almost exclusively on positive interpretations of links between people, we study how the interplay between positive and negative relationships affects the structure of on-line social networks. We connect our analyses to theories of signed networks from social psychology. We find that the c...

  20. Seven Deadliest Social Network Attacks

    CERN Document Server

    Timm, Carl

    2010-01-01

    Do you need to keep up with the latest hacks, attacks, and exploits effecting social networks? Then you need Seven Deadliest Social Network Attacks. This book pinpoints the most dangerous hacks and exploits specific to social networks like Facebook, Twitter, and MySpace, laying out the anatomy of these attacks including how to make your system more secure. You will discover the best ways to defend against these vicious hacks with step-by-step instruction and learn techniques to make your computer and network impenetrable. Attacks detailed in this book include: Social Networking Infrastruct

  1. Social Network Gaming Trends

    Directory of Open Access Journals (Sweden)

    Michael Gathwright

    2010-01-01

    Full Text Available The purpose of this project was to determine how long the social network game Scratch-Offs, created by game development company Spice Rack Media, will remain financially viable. The game Scratch-Offs is a freeware game (users pay nothing for the actual software and is funded through micro transactions (users must pay small amounts of money to play actual games. This implies a relationship between total games played and revenue earned. Using data provided by Spice Rack, we were able to develop an exponential equation that accurately depicts usage trends over time. This equation was used to determine the date Scratch-Offs will no longer be profitable.

  2. Elgg 18 Social Networking

    CERN Document Server

    Costello, Cash

    2012-01-01

    This book provides more than just a step-by-step guide to installing and using Elgg. It includes practical advice gained through experience on what it takes to deploy and maintain an Elgg-based site. If you are a software developer or are familiar with PHP, it provides both a tutorial-based introduction and a quick reference guide so that you can quickly extend and customize Elgg. If you want to create a social networking site using Elgg and do not have a background in software development, this book provides all the information and advice that you need written just for you. If you are a devel

  3. Privacy in Social Networks

    CERN Document Server

    Zheleva, Elena

    2012-01-01

    This synthesis lecture provides a survey of work on privacy in online social networks (OSNs). This work encompasses concerns of users as well as service providers and third parties. Our goal is to approach such concerns from a computer-science perspective, and building upon existing work on privacy, security, statistical modeling and databases to provide an overview of the technical and algorithmic issues related to privacy in OSNs. We start our survey by introducing a simple OSN data model and describe common statistical-inference techniques that can be used to infer potentially sensitive inf

  4. Social Networks and Technology Adoption

    OpenAIRE

    Hogset, Heidi

    2005-01-01

    This study analyzes social network effects on Kenyan smallholders' decision to adopt improved natural resource management techniques. These effects are decomposed into effects from social influence and learning through networks (strong ties), group effects, weak ties effects, informal finance, and conflicts arising from technological externalities, controlling for non-network effects.

  5. Underage Children and Social Networking

    Science.gov (United States)

    Weeden, Shalynn; Cooke, Bethany; McVey, Michael

    2013-01-01

    Despite minimum age requirements for joining popular social networking services such as Facebook, many students misrepresent their real ages and join as active participants in the networks. This descriptive study examines the use of social networking services (SNSs) by children under the age of 13. The researchers surveyed a sample of 199…

  6. On the design of a hierarchical SS7 network: A graph theoretical approach

    Science.gov (United States)

    Krauss, Lutz; Rufa, Gerhard

    1994-04-01

    This contribution is concerned with the design of Signaling System No. 7 networks based on graph theoretical methods. A hierarchical network topology is derived by combining the advantage of the hierarchical network structure with the realization of node disjoint routes between nodes of the network. By using specific features of this topology, we develop an algorithm to construct circle-free routing data and to assure bidirectionality also in case of failure situations. The methods described are based on the requirements that the network topology, as well as the routing data, may be easily changed.

  7. Online networks destroy social trust

    OpenAIRE

    Sabatini, Fabio; Sarracino, Francesco

    2014-01-01

    Studies in the social capital literature have documented two stylised facts: first, a decline in measures of social participation has occurred in many OECD countries. Second, and more recently, the success of social networking sites (SNSs) has resulted in a steep rise in online social participation. Our study adds to this body of research by conducting the first empirical assessment of how online networking affects two economically relevant aspects of social capital, i.e. trust and sociabilit...

  8. Statistical Models for Social Networks

    NARCIS (Netherlands)

    Snijders, Tom A. B.; Cook, KS; Massey, DS

    2011-01-01

    Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For

  9. Social Interaction in Learning Networks

    NARCIS (Netherlands)

    Sloep, Peter

    2009-01-01

    The original publication is available from www.springerlink.com. Sloep, P. (2009). Social Interaction in Learning Networks. In R. Koper (Ed.), Learning Network Services for Professional Development (pp 13-15). Berlin, Germany: Springer Verlag.

  10. On sampling social networking services

    OpenAIRE

    Wang, Baiyang

    2012-01-01

    This article aims at summarizing the existing methods for sampling social networking services and proposing a faster confidence interval for related sampling methods. It also includes comparisons of common network sampling techniques.

  11. Optimal Hierarchical Modular Topologies for Producing Limited Sustained Activation of Neural Networks

    OpenAIRE

    Kaiser, Marcus; Hilgetag, Claus C.

    2010-01-01

    An essential requirement for the representation of functional patterns in complex neural networks, such as the mammalian cerebral cortex, is the existence of stable regimes of network activation, typically arising from a limited parameter range. In this range of limited sustained activity (LSA), the activity of neural populations in the network persists between the extremes of either quickly dying out or activating the whole network. Hierarchical modular networks were previously found to show...

  12. Online social networking for radiology.

    Science.gov (United States)

    Auffermann, William F; Chetlen, Alison L; Colucci, Andrew T; DeQuesada, Ivan M; Grajo, Joseph R; Heller, Matthew T; Nowitzki, Kristina M; Sherry, Steven J; Tillack, Allison A

    2015-01-01

    Online social networking services have changed the way we interact as a society and offer many opportunities to improve the way we practice radiology and medicine in general. This article begins with an introduction to social networking. Next, the latest advances in online social networking are reviewed, and areas where radiologists and clinicians may benefit from these new tools are discussed. This article concludes with several steps that the interested reader can take to become more involved in online social networking. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

  13. Social support and social network as intermediary social determinants of dental caries in adolescents.

    Science.gov (United States)

    Fontanini, Humberto; Marshman, Zoe; Vettore, Mario

    2015-04-01

    The aim of this study was to investigate the association between intermediary social determinants, namely social support and social network with dental caries in adolescents. An adapted version of the WHO social determinants of health conceptual framework was used to organize structural and intermediary social determinants of dental caries into six blocks including perceived social support and number of social networks. A cross-sectional study was conducted with a representative sample of 542 students between 12 and 14 years of age in public schools located in the city of Dourados, Brazil in 2012. The outcome variables were caries experience (DMFT ≥ 1) and current dental caries (component D of DMFT ≥ 1) recorded by a calibrated dentist. Individual interviews were performed to collect data on perceived social support and numbers of social networks from family and friends and covariates. Multivariate Poisson regressions using hierarchical models were conducted. The prevalence of adolescents with caries experience and current dental caries was 55.2% and 32.1%, respectively. Adolescents with low numbers of social networks and low levels of social support from family (PR 1.47; 95% CI = 1.01-2.14) were more likely to have DMFT ≥ 1. Current dental caries was associated with low numbers of social networks and low levels of social support from family (PR 2.26; 95% CI = 1.15-4.44). Social support and social network were influential psychosocial factors to dental caries in adolescents. This finding requires confirmation in other countries but potentially has implications for programmes to promote oral health. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  14. Quantum social networks

    International Nuclear Information System (INIS)

    Cabello, Adán; López-Tarrida, Antonio J; Danielsen, Lars Eirik; Portillo, José R

    2012-01-01

    We introduce a physical approach to social networks (SNs) in which each actor is characterized by a yes–no test on a physical system. This allows us to consider SNs beyond those originated by interactions based on pre-existing properties, as in a classical SN (CSN). As an example of SNs beyond CSNs, we introduce quantum SNs (QSNs) in which actor i is characterized by a test of whether or not the system is in a quantum state |ψ i 〉. We show that QSNs outperform CSNs for a certain task and some graphs. We identify the simplest of these graphs and show that graphs in which QSNs outperform CSNs are increasingly frequent as the number of vertices increases. We also discuss more general SNs and identify the simplest graphs in which QSNs cannot be outperformed. (paper)

  15. Churn in Social Networks

    Science.gov (United States)

    Karnstedt, Marcel; Hennessy, Tara; Chan, Jeffrey; Basuchowdhuri, Partha; Hayes, Conor; Strufe, Thorsten

    In the past, churn has been identified as an issue across most industry sectors. In its most general sense it refers to the rate of loss of customers from a company's customer base. There is a simple reason for the attention churn attracts: churning customers mean a loss of revenue. Emerging from business spaces like telecommunications (telcom) and broadcast providers, where churn is a major issue, it is also regarded as a crucial problem in many other businesses, such as online games creators, but also online social networks and discussion sites. Companies aim at identifying the risk of churn in its early stages, as it is usually much cheaper to retain a customer than to try to win him or her back. If this risk can be accurately predicted, marketing departments can target customers efficiently with tailored incentives to prevent them from leaving.

  16. Hierarchical modular structure enhances the robustness of self-organized criticality in neural networks

    International Nuclear Information System (INIS)

    Wang Shengjun; Zhou Changsong

    2012-01-01

    One of the most prominent architecture properties of neural networks in the brain is the hierarchical modular structure. How does the structure property constrain or improve brain function? It is thought that operating near criticality can be beneficial for brain function. Here, we find that networks with modular structure can extend the parameter region of coupling strength over which critical states are reached compared to non-modular networks. Moreover, we find that one aspect of network function—dynamical range—is highest for the same parameter region. Thus, hierarchical modularity enhances robustness of criticality as well as function. However, too much modularity constrains function by preventing the neural networks from reaching critical states, because the modular structure limits the spreading of avalanches. Our results suggest that the brain may take advantage of the hierarchical modular structure to attain criticality and enhanced function. (paper)

  17. TiO2 nanowire-templated hierarchical nanowire network as water-repelling coating

    Science.gov (United States)

    Hang, Tian; Chen, Hui-Jiuan; Xiao, Shuai; Yang, Chengduan; Chen, Meiwan; Tao, Jun; Shieh, Han-ping; Yang, Bo-ru; Liu, Chuan; Xie, Xi

    2017-12-01

    Extraordinary water-repelling properties of superhydrophobic surfaces make them novel candidates for a great variety of potential applications. A general approach to achieve superhydrophobicity requires low-energy coating on the surface and roughness on nano- and micrometre scale. However, typical construction of superhydrophobic surfaces with micro-nano structure through top-down fabrication is restricted by sophisticated fabrication techniques and limited choices of substrate materials. Micro-nanoscale topographies templated by conventional microparticles through surface coating may produce large variations in roughness and uncontrollable defects, resulting in poorly controlled surface morphology and wettability. In this work, micro-nanoscale hierarchical nanowire network was fabricated to construct self-cleaning coating using one-dimensional TiO2 nanowires as microscale templates. Hierarchical structure with homogeneous morphology was achieved by branching ZnO nanowires on the TiO2 nanowire backbones through hydrothermal reaction. The hierarchical nanowire network displayed homogeneous micro/nano-topography, in contrast to hierarchical structure templated by traditional microparticles. This hierarchical nanowire network film exhibited high repellency to both water and cell culture medium after functionalization with fluorinated organic molecules. The hierarchical structure templated by TiO2 nanowire coating significantly increased the surface superhydrophobicity compared to vertical ZnO nanowires with nanotopography alone. Our results demonstrated a promising strategy of using nanowires as microscale templates for the rational design of hierarchical coatings with desired superhydrophobicity that can also be applied to various substrate materials.

  18. Social traits, social networks and evolutionary biology.

    Science.gov (United States)

    Fisher, D N; McAdam, A G

    2017-12-01

    The social environment is both an important agent of selection for most organisms, and an emergent property of their interactions. As an aggregation of interactions among members of a population, the social environment is a product of many sets of relationships and so can be represented as a network or matrix. Social network analysis in animals has focused on why these networks possess the structure they do, and whether individuals' network traits, representing some aspect of their social phenotype, relate to their fitness. Meanwhile, quantitative geneticists have demonstrated that traits expressed in a social context can depend on the phenotypes and genotypes of interacting partners, leading to influences of the social environment on the traits and fitness of individuals and the evolutionary trajectories of populations. Therefore, both fields are investigating similar topics, yet have arrived at these points relatively independently. We review how these approaches are diverged, and yet how they retain clear parallelism and so strong potential for complementarity. This demonstrates that, despite separate bodies of theory, advances in one might inform the other. Techniques in network analysis for quantifying social phenotypes, and for identifying community structure, should be useful for those studying the relationship between individual behaviour and group-level phenotypes. Entering social association matrices into quantitative genetic models may also reduce bias in heritability estimates, and allow the estimation of the influence of social connectedness on trait expression. Current methods for measuring natural selection in a social context explicitly account for the fact that a trait is not necessarily the property of a single individual, something the network approaches have not yet considered when relating network metrics to individual fitness. Harnessing evolutionary models that consider traits affected by genes in other individuals (i.e. indirect genetic

  19. Identifying time-delayed gene regulatory networks via an evolvable hierarchical recurrent neural network.

    Science.gov (United States)

    Kordmahalleh, Mina Moradi; Sefidmazgi, Mohammad Gorji; Harrison, Scott H; Homaifar, Abdollah

    2017-01-01

    The modeling of genetic interactions within a cell is crucial for a basic understanding of physiology and for applied areas such as drug design. Interactions in gene regulatory networks (GRNs) include effects of transcription factors, repressors, small metabolites, and microRNA species. In addition, the effects of regulatory interactions are not always simultaneous, but can occur after a finite time delay, or as a combined outcome of simultaneous and time delayed interactions. Powerful biotechnologies have been rapidly and successfully measuring levels of genetic expression to illuminate different states of biological systems. This has led to an ensuing challenge to improve the identification of specific regulatory mechanisms through regulatory network reconstructions. Solutions to this challenge will ultimately help to spur forward efforts based on the usage of regulatory network reconstructions in systems biology applications. We have developed a hierarchical recurrent neural network (HRNN) that identifies time-delayed gene interactions using time-course data. A customized genetic algorithm (GA) was used to optimize hierarchical connectivity of regulatory genes and a target gene. The proposed design provides a non-fully connected network with the flexibility of using recurrent connections inside the network. These features and the non-linearity of the HRNN facilitate the process of identifying temporal patterns of a GRN. Our HRNN method was implemented with the Python language. It was first evaluated on simulated data representing linear and nonlinear time-delayed gene-gene interaction models across a range of network sizes and variances of noise. We then further demonstrated the capability of our method in reconstructing GRNs of the Saccharomyces cerevisiae synthetic network for in vivo benchmarking of reverse-engineering and modeling approaches (IRMA). We compared the performance of our method to TD-ARACNE, HCC-CLINDE, TSNI and ebdbNet across different network

  20. A Social Networks in Education

    Science.gov (United States)

    Klimova, Blanka; Poulova, Petra

    2015-01-01

    At present social networks are becoming important in all areas of human activities. They are simply part and parcel of everyday life. They are mostly used for advertising, but they have already found their way into education. The future potential of social networks is high as it can be seen from their statistics on a daily, monthly or yearly…

  1. Social Networking Goes to School

    Science.gov (United States)

    Davis, Michelle R.

    2010-01-01

    Just a few years ago, social networking meant little more to educators than the headache of determining whether to penalize students for inappropriate activities captured on Facebook or MySpace. Now, teachers and students have an array of social-networking sites and tools--from Ning to VoiceThread and Second Life--to draw on for such serious uses…

  2. Risk aversion and social networks

    NARCIS (Netherlands)

    Kovářík, J.; van der Leij, M.J.

    2014-01-01

    This paper first investigates empirically the relationship between risk aversion and social network structure in a large group of undergraduate students. We find that risk aversion is strongly correlated to local network clustering, that is, the probability that one has a social tie to friends of

  3. Privacy in Online Social Networks

    NARCIS (Netherlands)

    Beye, Michael; Jeckmans, Arjan; Erkin, Zekeriya; Erkin, Zekeriya; Hartel, Pieter H.; Lagendijk, Reginald; Tang, Qiang; Abraham, A.

    Online Social Networks (OSNs) have become part of daily life for millions of users. Users building explicit networks that represent their social relationships and often share a wealth of personal information to their own benefit. The potential privacy risks of such behavior are often underestimated

  4. Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

    OpenAIRE

    Chih-Yu Wen; Ying-Chih Chen

    2009-01-01

    This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show t...

  5. Risk aversion and social networks

    NARCIS (Netherlands)

    Kovarik, J.; van der Leij, M.J.

    2011-01-01

    Agents involved in the formation of a social or economic network typically face uncertainty about the benefits of creating a link. However, the interplay of such uncertainty and risk attitudes has been neglected in the network formation literature. We propose a dynamic network formation model that

  6. Risk aversion and social networks

    NARCIS (Netherlands)

    Kovářík, J.; van der Leij, M.J.

    2012-01-01

    Agents involved in the formation of a social or economic network typically face uncertainty about the benefits of creating a link. However, the interplay of such uncertainty and risk attitudes has been neglected in the network formation literature. We propose a dynamic network formation model that

  7. A Hierarchical Approach to Real-time Activity Recognition in Body Sensor Networks

    DEFF Research Database (Denmark)

    Wang, Liang; Gu, Tao; Tao, Xianping

    2012-01-01

    Real-time activity recognition in body sensor networks is an important and challenging task. In this paper, we propose a real-time, hierarchical model to recognize both simple gestures and complex activities using a wireless body sensor network. In this model, we rst use a fast and lightweight al...

  8. Entropy of dynamical social networks

    Science.gov (United States)

    Zhao, Kun; Karsai, Marton; Bianconi, Ginestra

    2012-02-01

    Dynamical social networks are evolving rapidly and are highly adaptive. Characterizing the information encoded in social networks is essential to gain insight into the structure, evolution, adaptability and dynamics. Recently entropy measures have been used to quantify the information in email correspondence, static networks and mobility patterns. Nevertheless, we still lack methods to quantify the information encoded in time-varying dynamical social networks. In this talk we present a model to quantify the entropy of dynamical social networks and use this model to analyze the data of phone-call communication. We show evidence that the entropy of the phone-call interaction network changes according to circadian rhythms. Moreover we show that social networks are extremely adaptive and are modified by the use of technologies such as mobile phone communication. Indeed the statistics of duration of phone-call is described by a Weibull distribution and is significantly different from the distribution of duration of face-to-face interactions in a conference. Finally we investigate how much the entropy of dynamical social networks changes in realistic models of phone-call or face-to face interactions characterizing in this way different type human social behavior.

  9. Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations

    Science.gov (United States)

    Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong

    2010-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

  10. Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations

    Directory of Open Access Journals (Sweden)

    Sheng-Jun Wang

    2011-06-01

    Full Text Available Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. They are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality. We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. It was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We find that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and self-organized criticality, which are not present in the respective random networks. The underlying mechanism is that each dense module cannot sustain activity on its own, but displays self-organized criticality in the presence of weak perturbations. The hierarchical modular networks provide the coupling among subsystems with self-organized criticality. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivityof critical state and predictability and timing of oscillations for efficient

  11. Anti-Social Networking

    Directory of Open Access Journals (Sweden)

    Chris Allen

    2014-01-01

    Full Text Available With research highlighting the growing incidence of public opposition to the building of mosques and the innovative use of social networking, especially Facebook, to disseminate and garner support for such opposition, a pilot study sought to investigate this in relation to the proposed Dudley “super mosque.” Focusing on the Facebook group Stop Dudley Super Mosque and Islamic Village, members were engaged online to explore why they opposed the mosque. Some of the emergent themes included planning and location, inclusion and public investment as well as those relating to notions of identity, heritage, otherness, and Islamification. Overt racist and Islamophobic reasons were also identified. The sense of political disconnect of members is also considered. Concluding with a contextualization of the findings within the existing body of scholarly output, in particular the building of mosques and Islamophobia, having recognized how spaces such as Facebook have potential to function as sites for research and method also, an extended methodological consideration is also included.

  12. Staying Safe on Social Network Sites

    Science.gov (United States)

    ... Tips Security Tip (ST06-003) Staying Safe on Social Networking Sites Original release date: January 26, 2011 | Last revised: ... so you should take certain precautions. What are social networking sites? Social networking sites, sometimes referred to as "friend- ...

  13. Networks in social policy problems

    CERN Document Server

    Scotti, marco

    2012-01-01

    Network science is the key to managing social communities, designing the structure of efficient organizations and planning for sustainable development. This book applies network science to contemporary social policy problems. In the first part, tools of diffusion and team design are deployed to challenges in adoption of ideas and the management of creativity. Ideas, unlike information, are generated and adopted in networks of personal ties. Chapters in the second part tackle problems of power and malfeasance in political and business organizations, where mechanisms in accessing and controlling informal networks often outweigh formal processes. The third part uses ideas from biology and physics to understand global economic and financial crises, ecological depletion and challenges to energy security. Ideal for researchers and policy makers involved in social network analysis, business strategy and economic policy, it deals with issues ranging from what makes public advisories effective to how networks influenc...

  14. RECOMMENDER SYSTEMS IN SOCIAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Cleomar Valois Batista Jr

    2011-12-01

    Full Text Available The continued and diversified growth of social networks has changed the way in which users interact with them. With these changes, what once was limited to social contact is now used for exchanging ideas and opinions, creating the need for new features. Users have so much information at their fingertips that they are unable to process it by themselves; hence, the need to develop new tools. Recommender systems were developed to address this need and many techniques were used for different approaches to the problem. To make relevant recommendations, these systems use large sets of data, not taking the social network of the user into consideration. Developing a recommender system that takes into account the social network of the user is another way of tackling the problem. The purpose of this project is to use the theory of six degrees of separation (Watts 2003 amongst users of a social network to enhance existing recommender systems.

  15. SOCIAL NETWORKS AND INTERPERSONAL COMMUNICATION

    Directory of Open Access Journals (Sweden)

    Veronica GHEORGHIȚĂ

    2014-11-01

    Full Text Available Social networks visible influence people's ability to interact and communicate. Extending social circles by establishing virtual links involves a number of positive aspects such as: instant access to options for interaction, sharing of information to large communities of people, intensification of acts of communication, high levels of feedback and trust with people with whom we communicate. On the other hand, social networks adversely affects communication by decreasing the interaction face to face, by imposing superficial communications experiences, grammatical and spelling erosion of the language. Therefore, the study aims to capture the spread of social networks, their use and impact on interpersonal communication. More specifically, they look for the answer to the question: what is the nature of interpersonal communication that is found on social networking sites: personal, emotional, private or shared, informal, and public?

  16. Numerical analysis of a neural network with hierarchically organized patterns

    International Nuclear Information System (INIS)

    Bacci, Silvia; Wiecko, Cristina; Parga, Nestor

    1988-01-01

    A numerical analysis of the retrieval behaviour of an associative memory model where the memorized patterns are stored hierarchically is performed. It is found that the model is able to categorize errors. For a finite number of categories, these are retrieved correctly even when the stored patterns are not. Instead, when they are allowed to increase with the number of neurons, their retrieval quality deteriorates above a critical category capacity. (Author)

  17. Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chih-Yu Wen

    2009-05-01

    Full Text Available This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

  18. Dynamic hierarchical sleep scheduling for wireless ad-hoc sensor networks.

    Science.gov (United States)

    Wen, Chih-Yu; Chen, Ying-Chih

    2009-01-01

    This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

  19. Multiple dynamical time-scales in networks with hierarchically ...

    Indian Academy of Sciences (India)

    cists from resistor networks to polymer contact structure to spin interactions in disordered ... the intracellular signalling system to neuronal networks to ecological food ... tion of the key players can be used to develop drugs targeted specifically ...

  20. The Possibilities of Network Sociality

    Science.gov (United States)

    Willson, Michele

    Technologically networked social forms are broad, extensive and in demand. The rapid development and growth of web 2.0, or the social web, is evidence of the need and indeed hunger for social connectivity: people are searching for many and varied ways of enacting being-together. However, the ways in which we think of, research and write about network(ed) sociality are relatively recent and arguably restricted, warranting further critique and development. This article attempts to do several things: it raises questions about the types of sociality enacted in contemporary techno-society; critically explores the notion of the networked individual and the focus on the individual evident in much of the technology and sociality literature and asks questions about the place of the social in these discussions. It argues for a more well-balanced and multilevelled approach to questions of sociality in networked societies. The article starts from the position that possibilities enabled/afforded by the technologies we have in place have an effect upon the ways in which we understand being in the world together and our possible actions and futures. These possibilities are more than simply supplementary; in many ways they are transformative. The ways in which we grapple with these questions reveals as much about our understandings of sociality as it does about the technologies themselves.

  1. Loss Performance Modeling for Hierarchical Heterogeneous Wireless Networks With Speed-Sensitive Call Admission Control

    DEFF Research Database (Denmark)

    Huang, Qian; Huang, Yue-Cai; Ko, King-Tim

    2011-01-01

    . This approach avoids unnecessary and frequent handoff between cells and reduces signaling overheads. An approximation model with guaranteed accuracy and low computational complexity is presented for the loss performance of multiservice traffic. The accuracy of numerical results is validated by comparing......A hierarchical overlay structure is an alternative solution that integrates existing and future heterogeneous wireless networks to provide subscribers with better mobile broadband services. Traffic loss performance in such integrated heterogeneous networks is necessary for an operator's network...

  2. Semantic mining of social networks

    CERN Document Server

    Tang, Jie

    2015-01-01

    The first kinds of questions we try to answer are: What are the fundamental factors that form the different categories of social ties? How have reciprocal relationships been developed fro parasocial relationships? How do connected users further form groups? Another theme addressed in this book is the study of social influence. Social influence occurs when one's opinions, emotions, or behaviors are affected by others, intentionally or unintentionally. Considerable research has been conducted to verify the existence of social influence in various networks.

  3. The Social Life of Social Networks

    DEFF Research Database (Denmark)

    Robertson, Scott P.; Vatrapu, Ravi; Medina, Richard

    2009-01-01

    dialogues wished to send other participants. We show a strong integration of the Web 2.0 and new media technologies of social networking, online video, and blogs. Outside of video content, users tended to direct others to groups and applications within the Facebook community, but this homophilous behavior......This paper examines the linkage patterns of people who posted links on the Facebook “walls” of Barack Obama, Hillary Clinton, and John McCain over two years prior to the 2008 U.S. Presidential election. Linkage patterns indicate the destinations to which participants in these social networking...

  4. Online Identities and Social Networking

    Science.gov (United States)

    Maheswaran, Muthucumaru; Ali, Bader; Ozguven, Hatice; Lord, Julien

    Online identities play a critical role in the social web that is taking shape on the Internet. Despite many technical proposals for creating and managing online identities, none has received widespread acceptance. Design and implementation of online identities that are socially acceptable on the Internet remains an open problem. This chapter discusses the interplay between online identities and social networking. Online social networks (OSNs) are growing at a rapid pace and has millions of members in them. While the recent trend is to create explicit OSNs such as Facebook and MySpace, we also have implicit OSNs such as interaction graphs created by email and instant messaging services. Explicit OSNs allow users to create profiles and use them to project their identities on the web. There are many interesting identity related issues in the context of social networking including how OSNs help and hinder the definition of online identities.

  5. Using Hierarchical Temporal Memory for Detecting Anomalous Network Activity

    Science.gov (United States)

    2008-03-01

    warfare, computer network operations, psychological operations, military deception, and operations security, in concert with specified supporting and...you up short—you were subconsciously predicting something else and were surprised by the mismatch” [3]. Notable neurobiologist Horace Barlow of the...malicious network activity is flagged as abnormal . That is, test data should present the N-HTM network with spatial-temporal patterns that do not match 46

  6. Social Networks and Sales Performance

    Directory of Open Access Journals (Sweden)

    Danny Pimentel Claro

    2011-05-01

    Full Text Available This paper argues that an informal network can itself be a basis for the increase in a sales manager’s performance. Informal networks create a structure that surpasses the formal hierarchical structure defined by the firm. We concentrated on the advice network and considered two different views of network structure that claim to have impact on performance. To explore this claim, we examined whether sales managers develop either a highly cohesive network structure (i.e. Coleman’s view or one containing structural holes (i.e. Burt’s view in order to achieve higher sales. We also investigated the matter of tie strength put forward by Granovetter in his seminal 1973 work. Census data was collected from about 500 personnel from an agricultural input retailer having 23 divisions. Estimates from a sample of 101 sales managers showed the importance of a highly cohesive structure (degree centrality for the three measures of sales manager’s performance. The strong ties have a positive impact on performance, suggesting the importance of building up strong bonds with network contacts. Sales managers’ age, time within the retailer and education also influence performance. These results imply that firms should stimulate contacts among personnel to spread technical and commercial information.

  7. Measurement of Online Social Networks

    Science.gov (United States)

    Gjoka, Mina

    2010-01-01

    In recent years, the popularity of online social networks (OSN) has risen to unprecedented levels, with the most popular ones having hundreds of millions of users. This success has generated interest within the networking community and has given rise to a number of measurement and characterization studies, which provide a first step towards their…

  8. Social networks and research output

    NARCIS (Netherlands)

    Ductor, L.; Fafchamps, M.; Goyal, S.; van der Leij, M.J.

    2014-01-01

    We study how knowledge about the social network of an individual researcher - as embodied in his coauthor relations - helps us in developing a more accurate prediction of his future productivity. We find that incorporating information about coauthor networks leads to a modest improvement in the

  9. Social networks and factor markets

    DEFF Research Database (Denmark)

    Abay, Kibrom Araya; Kahsay, Goytom Abraha; Berhane, Guush

    In the absence of well-established factor markets, the role of indigenous institutions and social networks can be substantial for mobilizing factors for agricultural production. We investigate the role of an indigenous social network in Ethiopia, the iddir, in facilitating factor market...... transactions among smallholder farmers. Using detailed longitudinal household survey data and employing a difference-in-differences approach, we find that iddir membership improves households’ access to factor markets. Specifically, we find that joining an iddir network improves households’ access to land...

  10. A Hierarchical Approach to Persistent Scatterer Network Construction and Deformation Time Series Estimation

    Directory of Open Access Journals (Sweden)

    Rui Zhang

    2014-12-01

    Full Text Available This paper presents a hierarchical approach to network construction and time series estimation in persistent scatterer interferometry (PSI for deformation analysis using the time series of high-resolution satellite SAR images. To balance between computational efficiency and solution accuracy, a dividing and conquering algorithm (i.e., two levels of PS networking and solution is proposed for extracting deformation rates of a study area. The algorithm has been tested using 40 high-resolution TerraSAR-X images collected between 2009 and 2010 over Tianjin in China for subsidence analysis, and validated by using the ground-based leveling measurements. The experimental results indicate that the hierarchical approach can remarkably reduce computing time and memory requirements, and the subsidence measurements derived from the hierarchical solution are in good agreement with the leveling data.

  11. Exploring Neural Network Models with Hierarchical Memories and Their Use in Modeling Biological Systems

    Science.gov (United States)

    Pusuluri, Sai Teja

    Energy landscapes are often used as metaphors for phenomena in biology, social sciences and finance. Different methods have been implemented in the past for the construction of energy landscapes. Neural network models based on spin glass physics provide an excellent mathematical framework for the construction of energy landscapes. This framework uses a minimal number of parameters and constructs the landscape using data from the actual phenomena. In the past neural network models were used to mimic the storage and retrieval process of memories (patterns) in the brain. With advances in the field now, these models are being used in machine learning, deep learning and modeling of complex phenomena. Most of the past literature focuses on increasing the storage capacity and stability of stored patterns in the network but does not study these models from a modeling perspective or an energy landscape perspective. This dissertation focuses on neural network models both from a modeling perspective and from an energy landscape perspective. I firstly show how the cellular interconversion phenomenon can be modeled as a transition between attractor states on an epigenetic landscape constructed using neural network models. The model allows the identification of a reaction coordinate of cellular interconversion by analyzing experimental and simulation time course data. Monte Carlo simulations of the model show that the initial phase of cellular interconversion is a Poisson process and the later phase of cellular interconversion is a deterministic process. Secondly, I explore the static features of landscapes generated using neural network models, such as sizes of basins of attraction and densities of metastable states. The simulation results show that the static landscape features are strongly dependent on the correlation strength and correlation structure between patterns. Using different hierarchical structures of the correlation between patterns affects the landscape features

  12. The exact Laplacian spectrum for the Dyson hierarchical network.

    Science.gov (United States)

    Agliari, Elena; Tavani, Flavia

    2017-01-09

    We consider the Dyson hierarchical graph , that is a weighted fully-connected graph, where the pattern of weights is ruled by the parameter σ ∈ (1/2, 1]. Exploiting the deterministic recursivity through which is built, we are able to derive explicitly the whole set of the eigenvalues and the eigenvectors for its Laplacian matrix. Given that the Laplacian operator is intrinsically implied in the analysis of dynamic processes (e.g., random walks) occurring on the graph, as well as in the investigation of the dynamical properties of connected structures themselves (e.g., vibrational structures and relaxation modes), this result allows addressing analytically a large class of problems. In particular, as examples of applications, we study the random walk and the continuous-time quantum walk embedded in , the relaxation times of a polymer whose structure is described by , and the community structure of in terms of modularity measures.

  13. Eigenspaces of networks reveal the overlapping and hierarchical community structure more precisely

    International Nuclear Information System (INIS)

    Ma, Xiaoke; Gao, Lin; Yong, Xuerong

    2010-01-01

    Identifying community structure is fundamental for revealing the structure–functionality relationship in complex networks, and spectral algorithms have been shown to be powerful for this purpose. In a traditional spectral algorithm, each vertex of a network is embedded into a spectral space by making use of the eigenvectors of the adjacency matrix or Laplacian matrix of the graph. In this paper, a novel spectral approach for revealing the overlapping and hierarchical community structure of complex networks is proposed by not only using the eigenvalues and eigenvectors but also the properties of eigenspaces of the networks involved. This gives us a better characterization of community. We first show that the communicability between a pair of vertices can be rewritten in term of eigenspaces of a network. An agglomerative clustering algorithm is then presented to discover the hierarchical communities using the communicability matrix. Finally, these overlapping vertices are discovered with the corresponding eigenspaces, based on the fact that the vertices more densely connected amongst one another are more likely to be linked through short cycles. Compared with the traditional spectral algorithms, our algorithm can identify both the overlapping and hierarchical community without increasing the time complexity O(n 3 ), where n is the size of the network. Furthermore, our algorithm can also distinguish the overlapping vertices from bridges. The method is tested by applying it to some computer-generated and real-world networks. The experimental results indicate that our algorithm can reveal community structure more precisely than the traditional spectral approaches

  14. Detecting Hidden Hierarchy of Non Hierarchical Terrorist Networks

    DEFF Research Database (Denmark)

    Memon, Nasrullah

    measures (and combinations of them) to identify key players (important nodes) in terrorist networks. Our recently introduced techniques and algorithms (which are also implemented in the investigative data mining toolkit known as iMiner) will be particularly useful for law enforcement agencies that need...... to analyze terrorist networks and prioritize their targets. Applying recently introduced mathematical methods for constructing the hidden hierarchy of "nonhierarchical" terrorist networks; we present case studies of the terrorist attacks occurred / planned in the past, in order to identify hidden hierarchy...

  15. Brain networks of social comparison.

    Science.gov (United States)

    Kedia, Gayannée; Lindner, Michael; Mussweiler, Thomas; Ihssen, Niklas; Linden, David E J

    2013-03-27

    Social comparison, that is, the process of comparing oneself to other people, is a ubiquitous social cognitive mechanism; however, so far its neural correlates have remained unknown. The present study tested the hypothesis that social comparisons are supported by partly dissociated networks, depending on whether the dimension under comparison concerns a physical or a psychological attribute. We measured brain activity with functional MRI, whereas participants were comparing their own height or intelligence to that of individuals they personally know. Height comparisons were associated with higher activity in a frontoparietal network involved in spatial and numerical cognition. Conversely, intelligence comparisons recruited a network of midline areas that have been previously implicated in the attribution of mental states to oneself and others (Theory of mind). These findings suggest that social comparisons rely on diverse domain-specific mechanisms rather than on one unitary process.

  16. Unscrewing social media networks, twice

    DEFF Research Database (Denmark)

    Birkbak, Andreas

    2017-01-01

    Social media are often claimed to be an important new force in politics. One way to investigate such a claim is to follow an early call made in actor-network theory (ANT) to “unscrew” those entities that are assumed to be important and show how they are made up of heterogeneous networks of many...... different actors (Callon and Latour 1981). In this article I take steps towards unscrewing seven Facebook pages that were used to mobilize citizens for and against road pricing in Copenhagen in 2011-2012. But I encounter the difficulty that social media are already explicitly understood in Internet Studies...... that it can be combined with liberal notions of a singular public sphere (Somers 1995b; 1995a). In order to unscrew social media as a political force, I suggest that we need to work through both the assembling of social media networks and attend to corresponding reconstructions of liberal political narratives...

  17. Understanding Social Networks: Theories, Concepts, and Findings

    Science.gov (United States)

    Kadushin, Charles

    2012-01-01

    Despite the swift spread of social network concepts and their applications and the rising use of network analysis in social science, there is no book that provides a thorough general introduction for the serious reader. "Understanding Social Networks" fills that gap by explaining the big ideas that underlie the social network phenomenon.…

  18. Bottom-up GGM algorithm for constructing multiple layered hierarchical gene regulatory networks

    Science.gov (United States)

    Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways. A bottom-up graphic Gaus...

  19. On Hierarchical Extensions of Large-Scale 4-regular Grid Network Structures

    DEFF Research Database (Denmark)

    Pedersen, Jens Myrup; Patel, A.; Knudsen, Thomas Phillip

    It is studied how the introduction of ordered hierarchies in 4-regular grid network structures decreses distances remarkably, while at the same time allowing for simple topological routing schemes. Both meshes and tori are considered; in both cases non-hierarchical structures have power law depen...

  20. Relationship between Social Networks Adoption and Social Intelligence

    Science.gov (United States)

    Gunduz, Semseddin

    2017-01-01

    The purpose of this study was to set forth the relationship between the individuals' states to adopt social networks and social intelligence and analyze both concepts according to various variables. Research data were collected from 1145 social network users in the online media by using the Adoption of Social Network Scale and Social Intelligence…

  1. Extension of mixture-of-experts networks for binary classification of hierarchical data.

    Science.gov (United States)

    Ng, Shu-Kay; McLachlan, Geoffrey J

    2007-09-01

    For many applied problems in the context of medically relevant artificial intelligence, the data collected exhibit a hierarchical or clustered structure. Ignoring the interdependence between hierarchical data can result in misleading classification. In this paper, we extend the mechanism for mixture-of-experts (ME) networks for binary classification of hierarchical data. Another extension is to quantify cluster-specific information on data hierarchy by random effects via the generalized linear mixed-effects model (GLMM). The extension of ME networks is implemented by allowing for correlation in the hierarchical data in both the gating and expert networks via the GLMM. The proposed model is illustrated using a real thyroid disease data set. In our study, we consider 7652 thyroid diagnosis records from 1984 to early 1987 with complete information on 20 attribute values. We obtain 10 independent random splits of the data into a training set and a test set in the proportions 85% and 15%. The test sets are used to assess the generalization performance of the proposed model, based on the percentage of misclassifications. For comparison, the results obtained from the ME network with independence assumption are also included. With the thyroid disease data, the misclassification rate on test sets for the extended ME network is 8.9%, compared to 13.9% for the ME network. In addition, based on model selection methods described in Section 2, a network with two experts is selected. These two expert networks can be considered as modeling two groups of patients with high and low incidence rates. Significant variation among the predicted cluster-specific random effects is detected in the patient group with low incidence rate. It is shown that the extended ME network outperforms the ME network for binary classification of hierarchical data. With the thyroid disease data, useful information on the relative log odds of patients with diagnosed conditions at different periods can be

  2. A local adaptive algorithm for emerging scale-free hierarchical networks

    International Nuclear Information System (INIS)

    Gomez Portillo, I J; Gleiser, P M

    2010-01-01

    In this work we study a growing network model with chaotic dynamical units that evolves using a local adaptive rewiring algorithm. Using numerical simulations we show that the model allows for the emergence of hierarchical networks. First, we show that the networks that emerge with the algorithm present a wide degree distribution that can be fitted by a power law function, and thus are scale-free networks. Using the LaNet-vi visualization tool we present a graphical representation that reveals a central core formed only by hubs, and also show the presence of a preferential attachment mechanism. In order to present a quantitative analysis of the hierarchical structure we analyze the clustering coefficient. In particular, we show that as the network grows the clustering becomes independent of system size, and also presents a power law decay as a function of the degree. Finally, we compare our results with a similar version of the model that has continuous non-linear phase oscillators as dynamical units. The results show that local interactions play a fundamental role in the emergence of hierarchical networks.

  3. Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

    Science.gov (United States)

    Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

    2017-07-19

    Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

  4. Social networks and environmental outcomes.

    Science.gov (United States)

    Barnes, Michele L; Lynham, John; Kalberg, Kolter; Leung, PingSun

    2016-06-07

    Social networks can profoundly affect human behavior, which is the primary force driving environmental change. However, empirical evidence linking microlevel social interactions to large-scale environmental outcomes has remained scarce. Here, we leverage comprehensive data on information-sharing networks among large-scale commercial tuna fishers to examine how social networks relate to shark bycatch, a global environmental issue. We demonstrate that the tendency for fishers to primarily share information within their ethnic group creates segregated networks that are strongly correlated with shark bycatch. However, some fishers share information across ethnic lines, and examinations of their bycatch rates show that network contacts are more strongly related to fishing behaviors than ethnicity. Our findings indicate that social networks are tied to actions that can directly impact marine ecosystems, and that biases toward within-group ties may impede the diffusion of sustainable behaviors. Importantly, our analysis suggests that enhanced communication channels across segregated fisher groups could have prevented the incidental catch of over 46,000 sharks between 2008 and 2012 in a single commercial fishery.

  5. Hierarchical brain networks active in approach and avoidance goal pursuit.

    Science.gov (United States)

    Spielberg, Jeffrey M; Heller, Wendy; Miller, Gregory A

    2013-01-01

    Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal-pursuit processes (e.g., motivation) has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity) vital to goal-pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging) with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures.

  6. Social networks and bronchial asthma.

    Science.gov (United States)

    D'Amato, Gennaro; Cecchi, Lorenzo; Liccardi, Gennaro; D'Amato, Maria; Stanghellini, Giovanni

    2013-02-01

    To focus on both positive and negative aspects of the interaction between asthmatic patients and the social networks, and to highlight the need of a psychological approach in some individuals to integrate pharmacological treatment is the purpose of review. There is evidence that in some asthmatic patients, the excessive use of social networks can induce depression and stress triggering bronchial obstruction, whereas in others their rational use can induce beneficial effects in terms of asthma management. The increasing asthma prevalence in developed countries seen at the end of last century has raised concern for the considerable burden of this disease on society as well as individuals. Bronchial asthma is a disease in which psychological implications play a role in increasing or in reducing the severity of bronchial obstruction. Internet and, in particular, social media are increasingly a part of daily life of both young and adult people, thus allowing virtual relationships with peers sharing similar interests and goals. Although social network users often disclose more about themselves online than they do in person, there might be a risk for adolescents and for sensitive individuals, who can be negatively influenced by an incorrect use. However, although some studies show an increased risk of depression, other observations suggest beneficial effects of social networks by enhancing communication, social connection and self-esteem.

  7. Networks in Social Policy Problems

    Science.gov (United States)

    Vedres, Balázs; Scotti, Marco

    2012-08-01

    1. Introduction M. Scotti and B. Vedres; Part I. Information, Collaboration, Innovation: The Creative Power of Networks: 2. Dissemination of health information within social networks C. Dhanjal, S. Blanchemanche, S. Clemençon, A. Rona-Tas and F. Rossi; 3. Scientific teams and networks change the face of knowledge creation S. Wuchty, J. Spiro, B. F. Jones and B. Uzzi; 4. Structural folds: the innovative potential of overlapping groups B. Vedres and D. Stark; 5. Team formation and performance on nanoHub: a network selection challenge in scientific communities D. Margolin, K. Ognyanova, M. Huang, Y. Huang and N. Contractor; Part II. Influence, Capture, Corruption: Networks Perspectives on Policy Institutions: 6. Modes of coordination of collective action: what actors in policy making? M. Diani; 7. Why skewed distributions of pay for executives is the cause of much grief: puzzles and few answers so far B. Kogut and J.-S. Yang; 8. Networks of institutional capture: a case of business in the State apparatus E. Lazega and L. Mounier; 9. The social and institutional structure of corruption: some typical network configurations of corruption transactions in Hungary Z. Szántó, I. J. Tóth and S. Varga; Part III. Crisis, Extinction, World System Change: Network Dynamics on a Large Scale: 10. How creative elements help the recovery of networks after crisis: lessons from biology A. Mihalik, A. S. Kaposi, I. A. Kovács, T. Nánási, R. Palotai, Á. Rák, M. S. Szalay-Beko and P. Csermely; 11. Networks and globalization policies D. R. White; 12. Network science in ecology: the structure of ecological communities and the biodiversity question A. Bodini, S. Allesina and C. Bondavalli; 13. Supply security in the European natural gas pipeline network M. Scotti and B. Vedres; 14. Conclusions and outlook A.-L. Barabási; Index.

  8. Simulating individual-based models of epidemics in hierarchical networks

    NARCIS (Netherlands)

    Quax, R.; Bader, D.A.; Sloot, P.M.A.

    2009-01-01

    Current mathematical modeling methods for the spreading of infectious diseases are too simplified and do not scale well. We present the Simulator of Epidemic Evolution in Complex Networks (SEECN), an efficient simulator of detailed individual-based models by parameterizing separate dynamics

  9. Exploring hierarchical and overlapping modular structure in the yeast protein interaction network

    Directory of Open Access Journals (Sweden)

    Zhao Yi

    2010-12-01

    Full Text Available Abstract Background Developing effective strategies to reveal modular structures in protein interaction networks is crucial for better understanding of molecular mechanisms of underlying biological processes. In this paper, we propose a new density-based algorithm (ADHOC for clustering vertices of a protein interaction network using a novel subgraph density measurement. Results By statistically evaluating several independent criteria, we found that ADHOC could significantly improve the outcome as compared with five previously reported density-dependent methods. We further applied ADHOC to investigate the hierarchical and overlapping modular structure in the yeast PPI network. Our method could effectively detect both protein modules and the overlaps between them, and thus greatly promote the precise prediction of protein functions. Moreover, by further assaying the intermodule layer of the yeast PPI network, we classified hubs into two types, module hubs and inter-module hubs. Each type presents distinct characteristics both in network topology and biological functions, which could conduce to the better understanding of relationship between network architecture and biological implications. Conclusions Our proposed algorithm based on the novel subgraph density measurement makes it possible to more precisely detect hierarchical and overlapping modular structures in protein interaction networks. In addition, our method also shows a strong robustness against the noise in network, which is quite critical for analyzing such a high noise network.

  10. Navigating Social Networks

    Science.gov (United States)

    Hamblin, DeAnna; Bartlett, Marilyn J.

    2013-01-01

    The authors note that when it comes to balancing free speech and schools' responsibilities, the online world is largely uncharted waters. Questions remain about the rights of both students and teachers in the world of social media. Although the lower courts have ruled that students' freedom of speech rights offer them some protection for…

  11. Trust Transitivity in Social Networks

    OpenAIRE

    Richters, Oliver; Peixoto, Tiago P.

    2011-01-01

    Non-centralized recommendation-based decision making is a central feature of several social and technological processes, such as market dynamics, peer-to-peer file-sharing and the web of trust of digital certification. We investigate the properties of trust propagation on networks, based on a simple metric of trust transitivity. We investigate analytically the percolation properties of trust transitivity in random networks with arbitrary in/out-degree distributions, and compare with numerical...

  12. BRAND COMMUNICATION ON SOCIAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Otilia-Elena PLATON

    2015-07-01

    Full Text Available The communication represents a basic element for the marketing activity that helps companies to achieve their objectives. Building long-term relationships between brands and consumers is one of the most important objectives pursued by marketers. This involves brand communication and creating multiple connections with consumers, even in the online environment. From this point of view, social networks proved to be an effective way of linking brands and consumers online. This paper aims to present some aspects involved by the usage of social networks in brand communication by analyzing several examples of online marketing campaigns implemented on Facebook on the occasion of Valentine's Day by six different brands.

  13. Sleeping of a Complex Brain Networks with Hierarchical Organization

    Science.gov (United States)

    Zhang, Ying-Yue; Yang, Qiu-Ying; Chen, Tian-Lun

    2009-01-01

    The dynamical behavior in the cortical brain network of macaque is studied by modeling each cortical area with a subnetwork of interacting excitable neurons. We characterize the system by studying how to perform the transition, which is now topology-dependent, from the active state to that with no activity. This could be a naive model for the wakening and sleeping of a brain-like system, i.e., a multi-component system with two different dynamical behavior.

  14. Hierarchical brain networks active in approach and avoidance goal pursuit

    Directory of Open Access Journals (Sweden)

    Jeffrey Martin Spielberg

    2013-06-01

    Full Text Available Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal pursuit processes (e.g., motivation has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity vital to goal pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures.

  15. Social networks and factor markets

    DEFF Research Database (Denmark)

    Abay, Kibrom Araya; Kahsay, Goytom Abraha; Berhane, Guush

    2018-01-01

    We investigate the role of an indigenous social network in Ethiopia, the iddir, in facilitating factor market transactions among smallholder farmers. We use a detailed longitudinal household survey data and employ a fixed effects estimation to identify the effect of iddir membership on factor...... market transactions among farmers. We find that joining an iddir network improves households’ access to land, labour and credit transactions. Our findings also hint that iddir networks may crowd-out borrowing from local moneylenders (locally referred as ‘Arata Abedari’), a relatively expensive credit...

  16. Social networks user: current research

    OpenAIRE

    Agadullina E.R.

    2015-01-01

    The purpose of this article is to review current research studies focusing on the users of Facebook and their behaviors in social networks. This review is organized into two sections: 1) social-demographic characteristics (Age, Gender, Nationality); 2) personality characteristics (Neuroticism, Extraversion, Openness-to-Experience, Agreeableness, Conscientiousness, Narcissism, Self-esteem). The results showed that the information in the personal profile and online behavior are strongly connect...

  17. Social networks user: current research

    Directory of Open Access Journals (Sweden)

    Agadullina E.R.

    2015-12-01

    Full Text Available The purpose of this article is to review current research studies focusing on the users of Facebook and their behaviors in social networks. This review is organized into two sections: 1 social-demographic characteristics (Age, Gender, Nationality; 2 personality characteristics (Neuroticism, Extraversion, Openness-to-Experience, Agreeableness, Conscientiousness, Narcissism, Self-esteem. The results showed that the information in the personal profile and online behavior are strongly connected with socio-demographic and personality characteristics

  18. Socially Aware Heterogeneous Wireless Networks.

    Science.gov (United States)

    Kosmides, Pavlos; Adamopoulou, Evgenia; Demestichas, Konstantinos; Theologou, Michael; Anagnostou, Miltiades; Rouskas, Angelos

    2015-06-11

    The development of smart cities has been the epicentre of many researchers' efforts during the past decade. One of the key requirements for smart city networks is mobility and this is the reason stable, reliable and high-quality wireless communications are needed in order to connect people and devices. Most research efforts so far, have used different kinds of wireless and sensor networks, making interoperability rather difficult to accomplish in smart cities. One common solution proposed in the recent literature is the use of software defined networks (SDNs), in order to enhance interoperability among the various heterogeneous wireless networks. In addition, SDNs can take advantage of the data retrieved from available sensors and use them as part of the intelligent decision making process contacted during the resource allocation procedure. In this paper, we propose an architecture combining heterogeneous wireless networks with social networks using SDNs. Specifically, we exploit the information retrieved from location based social networks regarding users' locations and we attempt to predict areas that will be crowded by using specially-designed machine learning techniques. By recognizing possible crowded areas, we can provide mobile operators with recommendations about areas requiring datacell activation or deactivation.

  19. Social networks: communication and change

    Directory of Open Access Journals (Sweden)

    Gustavo Cardoso

    2011-01-01

    Full Text Available Virtual social networks have brought about the possibility for open and plural debate, where all those with the necessary literacy skills and means are able to participate in the creation and dissemination of information. By pressing political agents and determining the “agenda” of a lot of the media, users demonstrate that we stand at an ideal platform for creating both real social movements and more or less fleeting events, as manifestos or virtual campaigns. Nonetheless, in order to understand the role of virtual social networks in today’s world, we need to answer some prior questions. Are we facing a new communication model, whereby the product of “disinterested” interactivity creates an aura of confidence in disseminated information, often quite higher that that seen in the “old media”? Will that interactivity be a chance to fight-off citizens’ growing detachment with regard to the “res publica”? Will we find in citizen-made journalism, transmitted through virtual social networks, the consecration of a true fourth power? On the other hand, can we call the distinct collective movements we have seen emerging true “social movements”?The present article aims to examine this and other issues that come to the fore in the intricate social world of cyberspace.

  20. Hierarchical micro-mobility management in high-speed multihop access networks

    Institute of Scientific and Technical Information of China (English)

    TANG Bi-hua; MA Xiao-lei; LIU Yuan-an; GAO Jin-chun

    2006-01-01

    This article integrates the hierarchical micro-mobility management and the high-speed multihop access networks (HMAN), to accomplish the smooth handover between different access routers. The proposed soft handover scheme in the high-speed HMAN can solve the micro-mobility management problem in the access network. This article also proposes the hybrid access router (AR) advertisement scheme and AR selection algorithm, which uses the time delay and stable route to the AR as the gateway selection parameters. By simulation, the proposed micro-mobility management scheme can achieve high packet delivery fraction and improve the lifetime of network.

  1. Topology of the correlation networks among major currencies using hierarchical structure methods

    Science.gov (United States)

    Keskin, Mustafa; Deviren, Bayram; Kocakaplan, Yusuf

    2011-02-01

    We studied the topology of correlation networks among 34 major currencies using the concept of a minimal spanning tree and hierarchical tree for the full years of 2007-2008 when major economic turbulence occurred. We used the USD (US Dollar) and the TL (Turkish Lira) as numeraires in which the USD was the major currency and the TL was the minor currency. We derived a hierarchical organization and constructed minimal spanning trees (MSTs) and hierarchical trees (HTs) for the full years of 2007, 2008 and for the 2007-2008 period. We performed a technique to associate a value of reliability to the links of MSTs and HTs by using bootstrap replicas of data. We also used the average linkage cluster analysis for obtaining the hierarchical trees in the case of the TL as the numeraire. These trees are useful tools for understanding and detecting the global structure, taxonomy and hierarchy in financial data. We illustrated how the minimal spanning trees and their related hierarchical trees developed over a period of time. From these trees we identified different clusters of currencies according to their proximity and economic ties. The clustered structure of the currencies and the key currency in each cluster were obtained and we found that the clusters matched nicely with the geographical regions of corresponding countries in the world such as Asia or Europe. As expected the key currencies were generally those showing major economic activity.

  2. SOCIAL NETWORK EFFECTS ON ROMANTIC RELATIONSHIP

    Directory of Open Access Journals (Sweden)

    Fatma CAN

    2015-06-01

    Full Text Available The main objective of the study was to obtain information about social network variables in order to predict the relational commitment of married individuals and people having dating relationships. For this purpose, social network analysis has been carried out on 134 people having dating relationship and 154 married individuals and then Relationship Stability Scale, Subjective Norm Scale and Social Network Feature Survey prepared by the researcher were used. The results indicated that the approval of the closest social network member and the level of enjoyment of each other’s social network members had the best predictive value for relationship satisfaction and the investment to the relationship. The results also demonstrated that, approval of the social network had a negative impact on the level of the quality of alternatives and it showed that social networks were seen as a barrier function to have alternative relationships. Furthermore, by dividing social network members into two groups, for the dating group, the approval of the social network was the most significant variable for commitment but in the married group, the need for social network approval was not an important criteria because of having their relatioship already confirmed legally. When social network members were categorised and examined, the closest social network members did not differ by sex, but were varied in terms of relationship types. In the flirt group, one of their friends among his/her social network and their partners’ social network was specified as the closest social network member whereas in the married group, the closest social network member among his/her social network was their mother while it was their sibling among partner’s social network.

  3. Accurate detection of hierarchical communities in complex networks based on nonlinear dynamical evolution

    Science.gov (United States)

    Zhuo, Zhao; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng

    2018-04-01

    One of the most challenging problems in network science is to accurately detect communities at distinct hierarchical scales. Most existing methods are based on structural analysis and manipulation, which are NP-hard. We articulate an alternative, dynamical evolution-based approach to the problem. The basic principle is to computationally implement a nonlinear dynamical process on all nodes in the network with a general coupling scheme, creating a networked dynamical system. Under a proper system setting and with an adjustable control parameter, the community structure of the network would "come out" or emerge naturally from the dynamical evolution of the system. As the control parameter is systematically varied, the community hierarchies at different scales can be revealed. As a concrete example of this general principle, we exploit clustered synchronization as a dynamical mechanism through which the hierarchical community structure can be uncovered. In particular, for quite arbitrary choices of the nonlinear nodal dynamics and coupling scheme, decreasing the coupling parameter from the global synchronization regime, in which the dynamical states of all nodes are perfectly synchronized, can lead to a weaker type of synchronization organized as clusters. We demonstrate the existence of optimal choices of the coupling parameter for which the synchronization clusters encode accurate information about the hierarchical community structure of the network. We test and validate our method using a standard class of benchmark modular networks with two distinct hierarchies of communities and a number of empirical networks arising from the real world. Our method is computationally extremely efficient, eliminating completely the NP-hard difficulty associated with previous methods. The basic principle of exploiting dynamical evolution to uncover hidden community organizations at different scales represents a "game-change" type of approach to addressing the problem of community

  4. Privacy and Social Networking Sites

    Science.gov (United States)

    Timm, Dianne M.; Duven, Carolyn J.

    2008-01-01

    College students are relying on the Internet to make connections with other people every day. As the Internet has developed and grown, so have the capabilities for interaction. Social networking sites, a group of Web sites that provide people with the opportunity to create an online profile and to share that profile with others, are a part of…

  5. Social Networking: Keeping It Clean

    Science.gov (United States)

    Waters, John K.

    2011-01-01

    The need to maintain an unpolluted learning environment is no easy task for schools and districts that have incorporated social networking sites into their educational life. The staff and teachers at Blaine High School in Minnesota's Anoka-Hennepin District 11 had been considering the pros and cons of establishing a school Facebook page when the…

  6. Convergent evidence for hierarchical prediction networks from human electrocorticography and magnetoencephalography.

    Science.gov (United States)

    Phillips, Holly N; Blenkmann, Alejandro; Hughes, Laura E; Kochen, Silvia; Bekinschtein, Tristan A; Cam-Can; Rowe, James B

    2016-09-01

    We propose that sensory inputs are processed in terms of optimised predictions and prediction error signals within hierarchical neurocognitive models. The combination of non-invasive brain imaging and generative network models has provided support for hierarchical frontotemporal interactions in oddball tasks, including recent identification of a temporal expectancy signal acting on prefrontal cortex. However, these studies are limited by the need to invert magnetoencephalographic or electroencephalographic sensor signals to localise activity from cortical 'nodes' in the network, or to infer neural responses from indirect measures such as the fMRI BOLD signal. To overcome this limitation, we examined frontotemporal interactions estimated from direct cortical recordings from two human participants with cortical electrode grids (electrocorticography - ECoG). Their frontotemporal network dynamics were compared to those identified by magnetoencephalography (MEG) in forty healthy adults. All participants performed the same auditory oddball task with standard tones interspersed with five deviant tone types. We normalised post-operative electrode locations to standardised anatomic space, to compare across modalities, and inverted the MEG to cortical sources using the estimated lead field from subject-specific head models. A mismatch negativity signal in frontal and temporal cortex was identified in all subjects. Generative models of the electrocorticographic and magnetoencephalographic data were separately compared using the free-energy estimate of the model evidence. Model comparison confirmed the same critical features of hierarchical frontotemporal networks in each patient as in the group-wise MEG analysis. These features included bilateral, feedforward and feedback frontotemporal modulated connectivity, in addition to an asymmetric expectancy driving input on left frontal cortex. The invasive ECoG provides an important step in construct validation of the use of neural

  7. Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

    Science.gov (United States)

    Raskovic, Dejan

    Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.

  8. A hierarchical clustering scheme approach to assessment of IP-network traffic using detrended fluctuation analysis

    Science.gov (United States)

    Takuma, Takehisa; Masugi, Masao

    2009-03-01

    This paper presents an approach to the assessment of IP-network traffic in terms of the time variation of self-similarity. To get a comprehensive view in analyzing the degree of long-range dependence (LRD) of IP-network traffic, we use a hierarchical clustering scheme, which provides a way to classify high-dimensional data with a tree-like structure. Also, in the LRD-based analysis, we employ detrended fluctuation analysis (DFA), which is applicable to the analysis of long-range power-law correlations or LRD in non-stationary time-series signals. Based on sequential measurements of IP-network traffic at two locations, this paper derives corresponding values for the LRD-related parameter α that reflects the degree of LRD of measured data. In performing the hierarchical clustering scheme, we use three parameters: the α value, average throughput, and the proportion of network traffic that exceeds 80% of network bandwidth for each measured data set. We visually confirm that the traffic data can be classified in accordance with the network traffic properties, resulting in that the combined depiction of the LRD and other factors can give us an effective assessment of network conditions at different times.

  9. Spreading gossip in social networks

    Science.gov (United States)

    Lind, Pedro G.; da Silva, Luciano R.; Andrade, José S., Jr.; Herrmann, Hans J.

    2007-09-01

    We study a simple model of information propagation in social networks, where two quantities are introduced: the spread factor, which measures the average maximal reachability of the neighbors of a given node that interchange information among each other, and the spreading time needed for the information to reach such a fraction of nodes. When the information refers to a particular node at which both quantities are measured, the model can be taken as a model for gossip propagation. In this context, we apply the model to real empirical networks of social acquaintances and compare the underlying spreading dynamics with different types of scale-free and small-world networks. We find that the number of friendship connections strongly influences the probability of being gossiped. Finally, we discuss how the spread factor is able to be applied to other situations.

  10. Spreading gossip in social networks.

    Science.gov (United States)

    Lind, Pedro G; da Silva, Luciano R; Andrade, José S; Herrmann, Hans J

    2007-09-01

    We study a simple model of information propagation in social networks, where two quantities are introduced: the spread factor, which measures the average maximal reachability of the neighbors of a given node that interchange information among each other, and the spreading time needed for the information to reach such a fraction of nodes. When the information refers to a particular node at which both quantities are measured, the model can be taken as a model for gossip propagation. In this context, we apply the model to real empirical networks of social acquaintances and compare the underlying spreading dynamics with different types of scale-free and small-world networks. We find that the number of friendship connections strongly influences the probability of being gossiped. Finally, we discuss how the spread factor is able to be applied to other situations.

  11. Systemic risk and hierarchical transitions of financial networks

    Science.gov (United States)

    Nobi, Ashadun; Lee, Jae Woo

    2017-06-01

    In this paper, the change in topological hierarchy, which is measured by the minimum spanning tree constructed from the cross-correlations between the stock indices from the S & P 500 for 1998-2012 in a one year moving time window, was used to analyze a financial crisis. The hierarchy increased in all minor crises in the observation time window except for the sharp crisis of 2007-2008 when the global financial crisis occurred. The sudden increase in hierarchy just before the global financial crisis can be used for the early detection of an upcoming crisis. Clearly, the higher the hierarchy, the higher the threats to financial stability. The scaling relations were developed to observe the changes in hierarchy with the network topology. These scaling relations can also identify and quantify the financial crisis periods, and appear to contain the predictive power of an upcoming crisis.

  12. Social structure of Facebook networks

    Science.gov (United States)

    Traud, Amanda L.; Mucha, Peter J.; Porter, Mason A.

    2012-08-01

    We study the social structure of Facebook “friendship” networks at one hundred American colleges and universities at a single point in time, and we examine the roles of user attributes-gender, class year, major, high school, and residence-at these institutions. We investigate the influence of common attributes at the dyad level in terms of assortativity coefficients and regression models. We then examine larger-scale groupings by detecting communities algorithmically and comparing them to network partitions based on user characteristics. We thereby examine the relative importance of different characteristics at different institutions, finding for example that common high school is more important to the social organization of large institutions and that the importance of common major varies significantly between institutions. Our calculations illustrate how microscopic and macroscopic perspectives give complementary insights on the social organization at universities and suggest future studies to investigate such phenomena further.

  13. SocialBrowsing: Integrating Social Networks and Web Browsing

    National Research Council Canada - National Science Library

    Golbeck, Jennifer; Wasser, Michael M

    2007-01-01

    .... The extension is paired with services provided by social networking websites, analyzes the page's contents, and adds tooltips and highlighting to indicate when there is relevant social information...

  14. N-Doped carbon spheres with hierarchical micropore-nanosheet networks for high performance supercapacitors.

    Science.gov (United States)

    Wang, Shoupei; Zhang, Jianan; Shang, Pei; Li, Yuanyuan; Chen, Zhimin; Xu, Qun

    2014-10-18

    N-doped carbon spheres with hierarchical micropore-nanosheet networks (HPSCSs) were facilely fabricated by a one-step carbonization and activation process of N containing polymer spheres by KOH. With the synergy effect of the multiple structures, HPSCSs exhibit a very high specific capacitance of 407.9 F g(-1) at 1 mV s(-1) (1.2 times higher than that of porous carbon spheres) and a robust cycling stability for supercapacitors.

  15. Optimal Parameter for the Training of Multilayer Perceptron Neural Networks by Using Hierarchical Genetic Algorithm

    International Nuclear Information System (INIS)

    Orozco-Monteagudo, Maykel; Taboada-Crispi, Alberto; Gutierrez-Hernandez, Liliana

    2008-01-01

    This paper deals with the controversial topic of the selection of the parameters of a genetic algorithm, in this case hierarchical, used for training of multilayer perceptron neural networks for the binary classification. The parameters to select are the crossover and mutation probabilities of the control and parametric genes and the permanency percent. The results can be considered as a guide for using this kind of algorithm.

  16. Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

    OpenAIRE

    Ning Yu; Renjian Feng; Jiangwen Wan; Yinfeng Wu; Yang Yu

    2011-01-01

    In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initia...

  17. Strategies of Legitimacy Through Social Media: The Networked Strategy

    DEFF Research Database (Denmark)

    Castelló, Itziar; Etter, Michael; Nielsen, Finn Årup

    2016-01-01

    the concept of a networked legitimacy strategy. With this strategy, legitimacy is gained through participation in non-hierarchical open platforms and the co-construction of agendas. We explore the organizational transition needed to yield this new legitimacy approach. We argue that, in this context......How can corporations develop legitimacy when coping with stakeholders who have multiple, often conflicting sustainable development (SD) agendas? We address this question by conducting an in-depth longitudinal case study of a corporation's stakeholder engagement in social media and propose......, legitimacy gains may increase when firms are able to reduce the control over the engagements and relate non-hierarchically with their publics. We contribute to the extant literature on political corporate social responsibility and legitimacy by providing an understanding of a new context for engagement...

  18. An Energy Efficient Cooperative Hierarchical MIMO Clustering Scheme for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sungyoung Lee

    2011-12-01

    Full Text Available In this work, we present an energy efficient hierarchical cooperative clustering scheme for wireless sensor networks. Communication cost is a crucial factor in depleting the energy of sensor nodes. In the proposed scheme, nodes cooperate to form clusters at each level of network hierarchy ensuring maximal coverage and minimal energy expenditure with relatively uniform distribution of load within the network. Performance is enhanced by cooperative multiple-input multiple-output (MIMO communication ensuring energy efficiency for WSN deployments over large geographical areas. We test our scheme using TOSSIM and compare the proposed scheme with cooperative multiple-input multiple-output (CMIMO clustering scheme and traditional multihop Single-Input-Single-Output (SISO routing approach. Performance is evaluated on the basis of number of clusters, number of hops, energy consumption and network lifetime. Experimental results show significant energy conservation and increase in network lifetime as compared to existing schemes.

  19. Social inheritance can explain the structure of animal social networks

    Science.gov (United States)

    Ilany, Amiyaal; Akçay, Erol

    2016-01-01

    The social network structure of animal populations has major implications for survival, reproductive success, sexual selection and pathogen transmission of individuals. But as of yet, no general theory of social network structure exists that can explain the diversity of social networks observed in nature, and serve as a null model for detecting species and population-specific factors. Here we propose a simple and generally applicable model of social network structure. We consider the emergence of network structure as a result of social inheritance, in which newborns are likely to bond with maternal contacts, and via forming bonds randomly. We compare model output with data from several species, showing that it can generate networks with properties such as those observed in real social systems. Our model demonstrates that important observed properties of social networks, including heritability of network position or assortative associations, can be understood as consequences of social inheritance. PMID:27352101

  20. Interests diffusion in social networks

    Science.gov (United States)

    D'Agostino, Gregorio; D'Antonio, Fulvio; De Nicola, Antonio; Tucci, Salvatore

    2015-10-01

    We provide a model for diffusion of interests in Social Networks (SNs). We demonstrate that the topology of the SN plays a crucial role in the dynamics of the individual interests. Understanding cultural phenomena on SNs and exploiting the implicit knowledge about their members is attracting the interest of different research communities both from the academic and the business side. The community of complexity science is devoting significant efforts to define laws, models, and theories, which, based on acquired knowledge, are able to predict future observations (e.g. success of a product). In the mean time, the semantic web community aims at engineering a new generation of advanced services by defining constructs, models and methods, adding a semantic layer to SNs. In this context, a leapfrog is expected to come from a hybrid approach merging the disciplines above. Along this line, this work focuses on the propagation of individual interests in social networks. The proposed framework consists of the following main components: a method to gather information about the members of the social networks; methods to perform some semantic analysis of the Domain of Interest; a procedure to infer members' interests; and an interests evolution theory to predict how the interests propagate in the network. As a result, one achieves an analytic tool to measure individual features, such as members' susceptibilities and authorities. Although the approach applies to any type of social network, here it is has been tested against the computer science research community. The DBLP (Digital Bibliography and Library Project) database has been elected as test-case since it provides the most comprehensive list of scientific production in this field.

  1. Food: Transformation in Social Networks

    Directory of Open Access Journals (Sweden)

    Daria N. Karpova

    2014-01-01

    Full Text Available The modem network and digitalized society is full of social changes in various accustomed spheres of our lives including transformation in food practices. The author gives an example of the easiest way how to book food virtually and get it home this day according to tastes of a customer. Moreover the article represents new forms of specific societies existed in the Internet called food-blogs. This, on the author's mind, changes the traditional mechanism of people's choice. Food-blogs are analyzed through the prism of multifunctionalism and dynamics of food and trust. When the process of food preparing and eating attains new communicative functions. Moreover the author notes some social reasons why one user choses this or that food-blog. For instance, the popularity of blogger and network users trust, mostly «blinded». Beside the point, the conception of «trust» used in the text is based on science works of contemporary sociologist P. Sztompka. Both socialized and communicative functions of food are described through theories of R. Bart and G. Simmel. It is underlined in the text that food transforms and gains new qualities notin traditional ways we used to think but in social and cultural construction in virtual space and through network communication.

  2. Social Networking: It's Not What You Think

    Science.gov (United States)

    Jones, Kevin D.

    2010-01-01

    This slide presentation reviews some of the current uses of the social networking sites available on the internet. It list some of the skills that are now considered obsolete and reviews the major social networking sites.

  3. Complexities of social networks: A Physicist's perspective

    OpenAIRE

    Sen, Parongama

    2006-01-01

    The review is a survey of the present status of research in social networks highlighting the topics of small world property, degree distributions, community structure, assortativity, modelling, dynamics and searching in social networks.

  4. A bioscaffolding strategy for hierarchical zeolites with a nanotube-trimodal network.

    Science.gov (United States)

    Li, Guannan; Huang, Haibo; Yu, Bowen; Wang, Yun; Tao, Jiawei; Wei, Yingxu; Li, Shougui; Liu, Zhongmin; Xu, Yan; Xu, Ruren

    2016-02-01

    Hierarchical zeolite monoliths with multimodal porosity are of paramount importance as they open up new horizons for advanced applications. So far, hierarchical zeolites based on nanotube scaffolds have never been reported. Inspired by the organization of biominerals, we have developed a novel precursor scaffolding-solid phase crystallization strategy for hierarchical zeolites with a unique nanotube scaffolding architecture and nanotube-trimodal network, where biomolecular self-assembly (BSA) provides a scaffolding blueprint. By vapor-treating Sil-1 seeded precursor scaffolds, zeolite MFI nanotube scaffolds are self-generated, during which evolution phenomena such as segmented voids and solid bridges are observed, in agreement with the Kirkendall effect in a solid-phase crystallization system. The nanotube walls are made of intergrown single crystals rendering good mechanical stability. The inner diameter of the nanotube is tunable between 30 and 90 nm by varying the thickness of the precursor layers. Macropores enclosed by cross-linked nanotubes can be modulated by the choice of BSA. Narrow mesopores are formed by intergrown nanocrystals. Hierarchical ZSM-5 monoliths with nanotube (90 nm), micropore (0.55 nm), mesopore (2 nm) and macropore (700 nm) exhibit superior catalytic performance in the methanol-to-hydrocarbon (MTH) conversion compared to conventional ZSM-5. BSA remains intact after crystallization, allowing a higher level of organization and functionalization of the zeolite nanotube scaffolds. The current work may afford a versatile strategy for hierarchical zeolite monoliths with nanotube scaffolding architectures and a nanotube-multimodal network leading to self-supporting and active zeolite catalysts, and for applications beyond.

  5. Leveraging social networks for toxicovigilance.

    Science.gov (United States)

    Chary, Michael; Genes, Nicholas; McKenzie, Andrew; Manini, Alex F

    2013-06-01

    The landscape of drug abuse is shifting. Traditional means of characterizing these changes, such as national surveys or voluntary reporting by frontline clinicians, can miss changes in usage the emergence of novel drugs. Delays in detecting novel drug usage patterns make it difficult to evaluate public policy aimed at altering drug abuse. Increasingly, newer methods to inform frontline providers to recognize symptoms associated with novel drugs or methods of administration are needed. The growth of social networks may address this need. The objective of this manuscript is to introduce tools for using data from social networks to characterize drug abuse. We outline a structured approach to analyze social media in order to capture emerging trends in drug abuse by applying powerful methods from artificial intelligence, computational linguistics, graph theory, and agent-based modeling. First, we describe how to obtain data from social networks such as Twitter using publicly available automated programmatic interfaces. Then, we discuss how to use artificial intelligence techniques to extract content useful for purposes of toxicovigilance. This filtered content can be employed to generate real-time maps of drug usage across geographical regions. Beyond describing the real-time epidemiology of drug abuse, techniques from computational linguistics can uncover ways that drug discussions differ from other online conversations. Next, graph theory can elucidate the structure of networks discussing drug abuse, helping us learn what online interactions promote drug abuse and whether these interactions differ among drugs. Finally, agent-based modeling relates online interactions to psychological archetypes, providing a link between epidemiology and behavior. An analysis of social media discussions about drug abuse patterns with computational linguistics, graph theory, and agent-based modeling permits the real-time monitoring and characterization of trends of drugs of abuse. These

  6. Stable configurations in social networks

    Science.gov (United States)

    Bronski, Jared C.; DeVille, Lee; Ferguson, Timothy; Livesay, Michael

    2018-06-01

    We present and analyze a model of opinion formation on an arbitrary network whose dynamics comes from a global energy function. We study the global and local minimizers of this energy, which we call stable opinion configurations, and describe the global minimizers under certain assumptions on the friendship graph. We show a surprising result that the number of stable configurations is not necessarily monotone in the strength of connection in the social network, i.e. the model sometimes supports more stable configurations when the interpersonal connections are made stronger.

  7. Social Network Analysis and informal trade

    DEFF Research Database (Denmark)

    Walther, Olivier

    networks can be applied to better understand informal trade in developing countries, with a particular focus on Africa. The paper starts by discussing some of the fundamental concepts developed by social network analysis. Through a number of case studies, we show how social network analysis can...... illuminate the relevant causes of social patterns, the impact of social ties on economic performance, the diffusion of resources and information, and the exercise of power. The paper then examines some of the methodological challenges of social network analysis and how it can be combined with other...... approaches. The paper finally highlights some of the applications of social network analysis and their implications for trade policies....

  8. Brand marketing model on social networks

    OpenAIRE

    Jezukevičiūtė, Jolita; Davidavičienė, Vida

    2014-01-01

    Paper analyzes the brand and its marketing solutions on social networks. This analysis led to the creation of improved brand marketing model on social networks, which will contribute to the rapid and cheap organization brand recognition, increase competitive advantage and enhance consumer loyalty. Therefore, the brand and a variety of social networks are becoming a hot research area for brand marketing model on social networks. The world‘s most successful brand marketing models exploratory an...

  9. Social networking services: technologies and applications

    OpenAIRE

    Puzyrnyy, Oleksandr

    2011-01-01

    Puzyrnyy, Oleksandr. 2011. Social networking services: technologies and applications. Bachelor's Thesis. Kemi-Tornio University of Applied Sciences. Business and Culture. Pages 52. The aim of this thesis is to describe the concept of social networking, its technological base, business opportunities and future perspectives. The study discovers how social networks are made and which different purposes they might have. In addition, social networking is viewed as a part of business strategy o...

  10. Organizational Application of Social Networking Information Technologies

    Science.gov (United States)

    Reppert, Jeffrey R.

    2012-01-01

    The focus of this qualitative research study using the Delphi method is to provide a framework for leaders to develop their own social networks. By exploring concerns in four areas, leaders may be able to better plan, implement, and manage social networking systems in organizations. The areas addressed are: (a) social networking using…

  11. Hierarchical Markov Model in Life Insurance and Social Benefit Schemes

    Directory of Open Access Journals (Sweden)

    Jiwook Jang

    2018-06-01

    Full Text Available We explored the effect of the jump-diffusion process on a social benefit scheme consisting of life insurance, unemployment/disability benefits, and retirement benefits. To do so, we used a four-state Markov chain with multiple decrements. Assuming independent state-wise intensities taking the form of a jump-diffusion process and deterministic interest rates, we evaluated the prospective reserves for this scheme in which the individual is employed at inception. We then numerically demonstrated the state of the reserves for the scheme under jump-diffusion and non-jump-diffusion settings. By decomposing the reserve equation into five components, our numerical illustration indicated that an extension of the retirement age has a spillover effect that would increase government expenses for other social insurance programs. We also conducted sensitivity analyses and examined the total-reserves components by changing the relevant parameters of the transition intensities, which are the average jump-size parameter, average jump frequency, and diffusion parameters of the chosen states, with figures provided. Our computation revealed that the total reserve is most sensitive to changes in average jump frequency.

  12. Social Networks and Students' Orthography

    Directory of Open Access Journals (Sweden)

    E. Azizovic

    2017-12-01

    Full Text Available The paper studied spelling and technical errors of students on social networks (facebook, twitter, e-mail. Social networks have over the last decade become the primary means of communication, which have more than ever made real the idea of "one world - one village". Their usage is in the most part based on language, i.e. on the writing itself and reading of the same as its most complex parts. New aspects of the use of writing, which exclude handwriting, are already using some new writing platform, such as keyboards, smart - touch surfaces, etc., provide new opportunities for redefining, as well as challenges for the writings. This paper aims to give a modest contribution in this direction.

  13. Hierarchically Coordinated Power Management for Target Tracking in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Feng Juan

    2013-10-01

    Full Text Available Energy efficiency is very important for wireless sensor networks (WSNs since sensor nodes have a limited energy supply from a battery. So far, a lot research has focused on this issue, while less emphasis has been placed on the adaptive sleep time for each node with a consideration for the application constraints. In this paper, we propose a hierarchically coordinated power management (HCPM approach, which both addresses the energy conservation problem and reduces the packet forwarding delay for target tracking WSNs based on a virtual-grid-based network structure. We extend the network lifetime by adopting an adaptive sleep scheduling scheme that combines the local power management (PM and the adaptive coordinate PM strategies to schedule the activities of the sensor nodes at the surveillance stage. Furthermore, we propose a hierarchical structure for the tracking stage. Experimental results show that the proposed approach has a greater capability of extending the network lifetime while maintaining a short transmission delay when compared with the protocol which does not consider the application constraints in target tracking sensor networks.

  14. Organ trade using social networks

    OpenAIRE

    Waleed Alrogy; Dunia Jawdat; Muhannad Alsemari; Abdulrahman Alharbi; Abdullah Alasaad; Ali H Hajeer

    2016-01-01

    Organ transplantation is recognized worldwide as an effective treatment for organ failure. However, due to the increase in the number of patients requiring a transplant, a shortage of suitable organs for transplantation has become a global problem. Human organ trade is an illegal practice of buying or selling organs and is universally sentenced. The aim of this study was to search social network for organ trade and offerings in Saudi Arabia. The study was conducted from June 22, 2015 to Febru...

  15. Gender differences in social networks

    Directory of Open Access Journals (Sweden)

    Komaromi Bojana

    2014-01-01

    Full Text Available This paper examines gender differences in different types of social networks. One of the main concepts relevant for studying gender differences is homophily, which refers to the tendency of people to interact more with similar individuals. In this paper homophily is analysed within the structural perspective which explains that the structures of our networks depend primarily on opportunities for social interactions, i.e. the composition and dynamics of the social context in which these interactions are embedded. Homophily is evident among males and females as early as in childhood, only to be even more prominent in school and adult years. Sex segregation is probably the most evident in the organisational context, where it has detrimental effects on women's careers, as women are generally underrepresented in positions of power and authority. Research in the last two decades pointed to the facts: 1 that men and women have very different types of organisational networks, 2 that successful men and women adopt different strategies to reach similar career objectives and acquire similar resources, and 3 that organisations also need to be actively involved in solving these gender-related issues.

  16. From Offline Social Networks to Online Social Networks: Changes in Entrepreneurship

    Directory of Open Access Journals (Sweden)

    Yang SONG

    2015-01-01

    Full Text Available The paper reviewed studies of entrepreneurship based on the emergency of online social networks. Similar to offline social networks, entrepreneurs’ online social networks have their own unique characteristics. We first reviewed the offline network based research on entrepreneurship. Then we reviewed the studies of entrepreneurship in the context of online social networks including those focusing on topics of network structures and network ties. We highlighted online network communities based on the data collected from LinkedIn, Facebook and Twitter. Our research implies that both researcher and entrepreneurs are facing new opportunities due to the emergence of online social networks.

  17. Classifying dysmorphic syndromes by using artificial neural network based hierarchical decision tree.

    Science.gov (United States)

    Özdemir, Merve Erkınay; Telatar, Ziya; Eroğul, Osman; Tunca, Yusuf

    2018-05-01

    Dysmorphic syndromes have different facial malformations. These malformations are significant to an early diagnosis of dysmorphic syndromes and contain distinctive information for face recognition. In this study we define the certain features of each syndrome by considering facial malformations and classify Fragile X, Hurler, Prader Willi, Down, Wolf Hirschhorn syndromes and healthy groups automatically. The reference points are marked on the face images and ratios between the points' distances are taken into consideration as features. We suggest a neural network based hierarchical decision tree structure in order to classify the syndrome types. We also implement k-nearest neighbor (k-NN) and artificial neural network (ANN) classifiers to compare classification accuracy with our hierarchical decision tree. The classification accuracy is 50, 73 and 86.7% with k-NN, ANN and hierarchical decision tree methods, respectively. Then, the same images are shown to a clinical expert who achieve a recognition rate of 46.7%. We develop an efficient system to recognize different syndrome types automatically in a simple, non-invasive imaging data, which is independent from the patient's age, sex and race at high accuracy. The promising results indicate that our method can be used for pre-diagnosis of the dysmorphic syndromes by clinical experts.

  18. Energy Efficient Hierarchical Clustering Approaches in Wireless Sensor Networks: A Survey

    Directory of Open Access Journals (Sweden)

    Bilal Jan

    2017-01-01

    Full Text Available Wireless sensor networks (WSN are one of the significant technologies due to their diverse applications such as health care monitoring, smart phones, military, disaster management, and other surveillance systems. Sensor nodes are usually deployed in large number that work independently in unattended harsh environments. Due to constraint resources, typically the scarce battery power, these wireless nodes are grouped into clusters for energy efficient communication. In clustering hierarchical schemes have achieved great interest for minimizing energy consumption. Hierarchical schemes are generally categorized as cluster-based and grid-based approaches. In cluster-based approaches, nodes are grouped into clusters, where a resourceful sensor node is nominated as a cluster head (CH while in grid-based approach the network is divided into confined virtual grids usually performed by the base station. This paper highlights and discusses the design challenges for cluster-based schemes, the important cluster formation parameters, and classification of hierarchical clustering protocols. Moreover, existing cluster-based and grid-based techniques are evaluated by considering certain parameters to help users in selecting appropriate technique. Furthermore, a detailed summary of these protocols is presented with their advantages, disadvantages, and applicability in particular cases.

  19. Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

    Science.gov (United States)

    Colclough, Giles L; Woolrich, Mark W; Harrison, Samuel J; Rojas López, Pedro A; Valdes-Sosa, Pedro A; Smith, Stephen M

    2018-05-07

    A Bayesian model for sparse, hierarchical inverse covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fmri, meg and eeg data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in meg beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity. Copyright © 2018. Published by Elsevier Inc.

  20. Brand Marketing Model on Social Networks

    Directory of Open Access Journals (Sweden)

    Jolita Jezukevičiūtė

    2014-04-01

    Full Text Available The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalysis of a single case study revealed a brand marketingsocial networking tools that affect consumers the most. Basedon information analysis and methodological studies, develop abrand marketing model on social networks.

  1. Handbook of social network technologies and applications

    CERN Document Server

    Furht, Borko

    2010-01-01

    Social networking is a concept that has existed for a long time; however, with the explosion of the Internet, social networking has become a tool for people to connect and communicate in ways that were impossible in the past. The recent development of Web 2.0 has provided many new applications, such as Myspace, Facebook, and LinkedIn. The purpose of ""Handbook of Social Networks: Technologies and Applications"" is to provide comprehensive guidelines on the current and future trends in social network technologies and applications in the field of Web-based Social Networks. This handbook includes

  2. Networking, or What the Social Means in Social Media

    OpenAIRE

    Taina Bucher

    2015-01-01

    This article questions the meaning of the social in social media. It does this by revisiting boyd and Ellison’s seminal paper and definition of social network sites. The article argues that social media are not so much about articulating or making an existing network visible. Rather, being social in the context of social media simply means creating connections within the boundaries of adaptive algorithmic architectures. Every click, share, like, and post creates a connection, initiates a rela...

  3. Using Social Network Research in HRM

    DEFF Research Database (Denmark)

    Kaše, Robert; King, Zella; Minbaeva, Dana

    2013-01-01

    ; the impact of social networking sites on perceptions of relationships; and ethical issues in organizational network analysis, we propose specific suggestions to bring social network perspectives closer to HRM researchers and practitioners and rebalance our attention to people and to their relationships.......The article features a conversation between Rob Cross and Martin Kilduff about organizational network analysis in research and practice. It demonstrates the value of using social network perspectives in HRM. Drawing on the discussion about managing personal networks; managing the networks of others...

  4. A Hybrid P2P Overlay Network for Non-strictly Hierarchically Categorized Content

    Science.gov (United States)

    Wan, Yi; Asaka, Takuya; Takahashi, Tatsuro

    In P2P content distribution systems, there are many cases in which the content can be classified into hierarchically organized categories. In this paper, we propose a hybrid overlay network design suitable for such content called Pastry/NSHCC (Pastry for Non-Strictly Hierarchically Categorized Content). The semantic information of classification hierarchies of the content can be utilized regardless of whether they are in a strict tree structure or not. By doing so, the search scope can be restrained to any granularity, and the number of query messages also decreases while maintaining keyword searching availability. Through simulation, we showed that the proposed method provides better performance and lower overhead than unstructured overlays exploiting the same semantic information.

  5. Hierarchical self-assembly of a striped gyroid formed by threaded chiral mesoscale networks

    DEFF Research Database (Denmark)

    Kirkensgaard, Jacob Judas Kain; Evans, Myfanwy; de Campo, Lilliana

    2014-01-01

    Numerical simulations reveal a family of hierarchical and chiral multicontinuous network structures self-assembled from a melt blend of Y-shaped ABC and ABD three-miktoarm star terpolymers, constrained to have equal-sized A/B and C/D chains, respectively. The C and D majority domains within...... components also forming labyrinthine domains whose geometry and topology changes systematically as a function of composition. These smaller labyrinths are well described by a family of patterns that tile the hyperbolic plane by regular degree-three trees mapped onto the gyroid. The labyrinths within......-ridden achiral patterns, containing domains of either hand, due to the achiral terpolymeric starting molecules. These mesostructures are among the most topologically complex morphologies identified to date and represent an example of hierarchical ordering within a hyperbolic pattern, a unique mode of soft...

  6. TWO-LEVEL HIERARCHICAL COORDINATION QUEUING METHOD FOR TELECOMMUNICATION NETWORK NODES

    Directory of Open Access Journals (Sweden)

    M. V. Semenyaka

    2014-07-01

    Full Text Available The paper presents hierarchical coordination queuing method. Within the proposed method a queuing problem has been reduced to optimization problem solving that was presented as two-level hierarchical structure. The required distribution of flows and bandwidth allocation was calculated at the first level independently for each macro-queue; at the second level solutions obtained on lower level for each queue were coordinated in order to prevent probable network link overload. The method of goal coordination has been determined for multilevel structure managing, which makes it possible to define the order for consideration of queue cooperation restrictions and calculation tasks distribution between levels of hierarchy. Decisions coordination was performed by the method of Lagrange multipliers. The study of method convergence has been carried out by analytical modeling.

  7. Visualization and Hierarchical Analysis of Flow in Discrete Fracture Network Models

    Science.gov (United States)

    Aldrich, G. A.; Gable, C. W.; Painter, S. L.; Makedonska, N.; Hamann, B.; Woodring, J.

    2013-12-01

    Flow and transport in low permeability fractured rock is primary in interconnected fracture networks. Prediction and characterization of flow and transport in fractured rock has important implications in underground repositories for hazardous materials (eg. nuclear and chemical waste), contaminant migration and remediation, groundwater resource management, and hydrocarbon extraction. We have developed methods to explicitly model flow in discrete fracture networks and track flow paths using passive particle tracking algorithms. Visualization and analysis of particle trajectory through the fracture network is important to understanding fracture connectivity, flow patterns, potential contaminant pathways and fast paths through the network. However, occlusion due to the large number of highly tessellated and intersecting fracture polygons preclude the effective use of traditional visualization methods. We would also like quantitative analysis methods to characterize the trajectory of a large number of particle paths. We have solved these problems by defining a hierarchal flow network representing the topology of particle flow through the fracture network. This approach allows us to analyses the flow and the dynamics of the system as a whole. We are able to easily query the flow network, and use paint-and-link style framework to filter the fracture geometry and particle traces based on the flow analytics. This allows us to greatly reduce occlusion while emphasizing salient features such as the principal transport pathways. Examples are shown that demonstrate the methodology and highlight how use of this new method allows quantitative analysis and characterization of flow and transport in a number of representative fracture networks.

  8. Brand Marketing Model on Social Networks

    OpenAIRE

    Jolita Jezukevičiūtė; Vida Davidavičienė

    2014-01-01

    The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalys...

  9. The model of social crypto-network

    Directory of Open Access Journals (Sweden)

    Марк Миколайович Орел

    2015-06-01

    Full Text Available The article presents the theoretical model of social network with the enhanced mechanism of privacy policy. It covers the problems arising in the process of implementing the mentioned type of network. There are presented the methods of solving problems arising in the process of building the social network with privacy policy. It was built a theoretical model of social networks with enhanced information protection methods based on information and communication blocks

  10. Social networks and employment in India

    OpenAIRE

    Tushar K. Nandi

    2010-01-01

    We investigate the influence of social networks on employment. Using data from India, we estimate the effect of caste based social networks on employment. We use a methodology that allows us to control for several omitted variable biases that often confound network effect. Our results indicate that caste based social networks are important determinant of employment in India. The implication of our findings is that a policy of positive discrimination in labour market for disadvantaged caste is...

  11. Human capital, social capital and scientific research in Europe: an application of linear hierarchical models

    OpenAIRE

    Mathieu Goudard; Michel Lubrano

    2011-01-01

    The theory of human capital is one way to explain individual decisions to produce scientific research. However, this theory, even if it reckons the importance of time in science, is too short for explaining the existing diversity of scientific output. The present paper introduces the social capital of Bourdieu (1980), Coleman (1988) and Putnam (1995) as a necessary complement to explain the creation of scientific human capital. This paper connects these two concepts by means of a hierarchical...

  12. Integration of relational and hierarchical network information for protein function prediction

    Directory of Open Access Journals (Sweden)

    Jiang Xiaoyu

    2008-08-01

    Full Text Available Abstract Background In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions. Results We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing. Conclusion A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased

  13. A Hierarchical Energy Efficient Reliable Transport Protocol for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Prabhudutta Mohanty

    2014-12-01

    Full Text Available The two important requirements for many Wireless Senor Networks (WSNs are prolonged network lifetime and end-to-end reliability. The sensor nodes consume more energy during data transmission than the data sensing. In WSN, the redundant data increase the energy consumption, latency and reduce reliability during data transmission. Therefore, it is important to support energy efficient reliable data transport in WSNs. In this paper, we present a Hierarchical Energy Efficient Reliable Transport Protocol (HEERTP for the data transmission within the WSN. This protocol maximises the network lifetime by controlling the redundant data transmission with the co-ordination of Base Station (BS. The proposed protocol also achieves end-to-end reliability using a hop-by-hop acknowledgement scheme. We evaluate the performance of the proposed protocol through simulation. The simulation results reveal that our proposed protocol achieves better performance in terms of energy efficiency, latency and reliability than the existing protocols.

  14. Enhanced fuzzy-connective-based hierarchical aggregation network using particle swarm optimization

    Science.gov (United States)

    Wang, Fang-Fang; Su, Chao-Ton

    2014-11-01

    The fuzzy-connective-based aggregation network is similar to the human decision-making process. It is capable of aggregating and propagating degrees of satisfaction of a set of criteria in a hierarchical manner. Its interpreting ability and transparency make it especially desirable. To enhance its effectiveness and further applicability, a learning approach is successfully developed based on particle swarm optimization to determine the weights and parameters of the connectives in the network. By experimenting on eight datasets with different characteristics and conducting further statistical tests, it has been found to outperform the gradient- and genetic algorithm-based learning approaches proposed in the literature; furthermore, it is capable of generating more accurate estimates. The present approach retains the original benefits of fuzzy-connective-based aggregation networks and is widely applicable. The characteristics of the learning approaches are also discussed and summarized, providing better understanding of the similarities and differences among these three approaches.

  15. Structure-function relationship in complex brain networks expressed by hierarchical synchronization

    International Nuclear Information System (INIS)

    Zhou Changsong; Zemanova, Lucia; Zamora-Lopez, Gorka; Hilgetag, Claus C; Kurths, Juergen

    2007-01-01

    The brain is one of the most complex systems in nature, with a structured complex connectivity. Recently, large-scale corticocortical connectivities, both structural and functional, have received a great deal of research attention, especially using the approach of complex network analysis. Understanding the relationship between structural and functional connectivity is of crucial importance in neuroscience. Here we try to illuminate this relationship by studying synchronization dynamics in a realistic anatomical network of cat cortical connectivity. We model the nodes (cortical areas) by a neural mass model (population model) or by a subnetwork of interacting excitable neurons (multilevel model). We show that if the dynamics is characterized by well-defined oscillations (neural mass model and subnetworks with strong couplings), the synchronization patterns are mainly determined by the node intensity (total input strengths of a node) and the detailed network topology is rather irrelevant. On the other hand, the multilevel model with weak couplings displays more irregular, biologically plausible dynamics, and the synchronization patterns reveal a hierarchical cluster organization in the network structure. The relationship between structural and functional connectivity at different levels of synchronization is explored. Thus, the study of synchronization in a multilevel complex network model of cortex can provide insights into the relationship between network topology and functional organization of complex brain networks

  16. Structure-function relationship in complex brain networks expressed by hierarchical synchronization

    Energy Technology Data Exchange (ETDEWEB)

    Zhou Changsong [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany); Zemanova, Lucia [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany); Zamora-Lopez, Gorka [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany); Hilgetag, Claus C [Jacobs University Bremen, Campus Ring 6, Rm 116, D-28759 Bremen (Germany); Kurths, Juergen [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany)

    2007-06-15

    The brain is one of the most complex systems in nature, with a structured complex connectivity. Recently, large-scale corticocortical connectivities, both structural and functional, have received a great deal of research attention, especially using the approach of complex network analysis. Understanding the relationship between structural and functional connectivity is of crucial importance in neuroscience. Here we try to illuminate this relationship by studying synchronization dynamics in a realistic anatomical network of cat cortical connectivity. We model the nodes (cortical areas) by a neural mass model (population model) or by a subnetwork of interacting excitable neurons (multilevel model). We show that if the dynamics is characterized by well-defined oscillations (neural mass model and subnetworks with strong couplings), the synchronization patterns are mainly determined by the node intensity (total input strengths of a node) and the detailed network topology is rather irrelevant. On the other hand, the multilevel model with weak couplings displays more irregular, biologically plausible dynamics, and the synchronization patterns reveal a hierarchical cluster organization in the network structure. The relationship between structural and functional connectivity at different levels of synchronization is explored. Thus, the study of synchronization in a multilevel complex network model of cortex can provide insights into the relationship between network topology and functional organization of complex brain networks.

  17. Psychology and social networks: a dynamic network theory perspective.

    Science.gov (United States)

    Westaby, James D; Pfaff, Danielle L; Redding, Nicholas

    2014-04-01

    Research on social networks has grown exponentially in recent years. However, despite its relevance, the field of psychology has been relatively slow to explain the underlying goal pursuit and resistance processes influencing social networks in the first place. In this vein, this article aims to demonstrate how a dynamic network theory perspective explains the way in which social networks influence these processes and related outcomes, such as goal achievement, performance, learning, and emotional contagion at the interpersonal level of analysis. The theory integrates goal pursuit, motivation, and conflict conceptualizations from psychology with social network concepts from sociology and organizational science to provide a taxonomy of social network role behaviors, such as goal striving, system supporting, goal preventing, system negating, and observing. This theoretical perspective provides psychologists with new tools to map social networks (e.g., dynamic network charts), which can help inform the development of change interventions. Implications for social, industrial-organizational, and counseling psychology as well as conflict resolution are discussed, and new opportunities for research are highlighted, such as those related to dynamic network intelligence (also known as cognitive accuracy), levels of analysis, methodological/ethical issues, and the need to theoretically broaden the study of social networking and social media behavior. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

  18. Hierarchical neural network model of the visual system determining figure/ground relation

    Science.gov (United States)

    Kikuchi, Masayuki

    2017-07-01

    One of the most important functions of the visual perception in the brain is figure/ground interpretation from input images. Figural region in 2D image corresponding to object in 3D space are distinguished from background region extended behind the object. Previously the author proposed a neural network model of figure/ground separation constructed on the standpoint that local geometric features such as curvatures and outer angles at corners are extracted and propagated along input contour in a single layer network (Kikuchi & Akashi, 2001). However, such a processing principle has the defect that signal propagation requires manyiterations despite the fact that actual visual system determines figure/ground relation within the short period (Zhou et al., 2000). In order to attain speed-up for determining figure/ground, this study incorporates hierarchical architecture into the previous model. This study confirmed the effect of the hierarchization as for the computation time by simulation. As the number of layers increased, the required computation time reduced. However, such speed-up effect was saturatedas the layers increased to some extent. This study attempted to explain this saturation effect by the notion of average distance between vertices in the area of complex network, and succeeded to mimic the saturation effect by computer simulation.

  19. An Efficient, Hierarchical Viewpoint Planning Strategy for Terrestrial Laser Scanner Networks

    Science.gov (United States)

    Jia, F.; Lichti, D. D.

    2018-05-01

    Terrestrial laser scanner (TLS) techniques have been widely adopted in a variety of applications. However, unlike in geodesy or photogrammetry, insufficient attention has been paid to the optimal TLS network design. It is valuable to develop a complete design system that can automatically provide an optimal plan, especially for high-accuracy, large-volume scanning networks. To achieve this goal, one should look at the "optimality" of the solution as well as the computational complexity in reaching it. In this paper, a hierarchical TLS viewpoint planning strategy is developed to solve the optimal scanner placement problems. If one targeted object to be scanned is simplified as discretized wall segments, any possible viewpoint can be evaluated by a score table representing its visible segments under certain scanning geometry constraints. Thus, the design goal is to find a minimum number of viewpoints that achieves complete coverage of all wall segments. The efficiency is improved by densifying viewpoints hierarchically, instead of a "brute force" search within the entire workspace. The experiment environments in this paper were simulated from two buildings located on University of Calgary campus. Compared with the "brute force" strategy in terms of the quality of the solutions and the runtime, it is shown that the proposed strategy can provide a scanning network with a compatible quality but with more than a 70 % time saving.

  20. Connecting Mobile Users Through Mobile Social Networks

    Directory of Open Access Journals (Sweden)

    Faisal Alkhateeb

    2012-10-01

    Full Text Available Nowadays, social networks become popular with the emerging of web-based social networking services. Recently, several mobile services are developed to connect users to their favourite social networks such as Facebook, Twitter, Flickr, etc. However, these services depends upon the existing web-based social networks. In this paper, we present a mobile service for joining groups across communities. The originality of the work is that the framework of the service allows creating and joining social networks that are self-contained for mobile company servers. The service consists of several sub-services such as users invitation, group finding and others. Users, regardless of their disability, can use the service and its sub-services without the need to create their own accounts on social web sites and thus their own groups. We also propose a privacy control policy for mobile social networks.

  1. A Social Network Analysis of Occupational Segregation

    DEFF Research Database (Denmark)

    Buhai, Ioan Sebastian; van der Leij, Marco

    We develop a social network model of occupational segregation between different social groups, generated by the existence of positive inbreeding bias among individuals from the same group. If network referrals are important for job search, then expected homophily in the contact network structure...

  2. Egocentric Social Network Analysis of Pathological Gambling

    Science.gov (United States)

    Meisel, Matthew K.; Clifton, Allan D.; MacKillop, James; Miller, Joshua D.; Campbell, W. Keith; Goodie, Adam S.

    2012-01-01

    Aims To apply social network analysis (SNA) to investigate whether frequency and severity of gambling problems were associated with different network characteristics among friends, family, and co-workers. is an innovative way to look at relationships among individuals; the current study was the first to our knowledge to apply SNA to gambling behaviors. Design Egocentric social network analysis was used to formally characterize the relationships between social network characteristics and gambling pathology. Setting Laboratory-based questionnaire and interview administration. Participants Forty frequent gamblers (22 non-pathological gamblers, 18 pathological gamblers) were recruited from the community. Findings The SNA revealed significant social network compositional differences between the two groups: pathological gamblers (PGs) had more gamblers, smokers, and drinkers in their social networks than did nonpathological gamblers (NPGs). PGs had more individuals in their network with whom they personally gambled, smoked, and drank with than those with who were NPG. Network ties were closer to individuals in their networks who gambled, smoked, and drank more frequently. Associations between gambling severity and structural network characteristics were not significant. Conclusions Pathological gambling is associated with compositional but not structural differences in social networks. Pathological gamblers differ from non-pathological gamblers in the number of gamblers, smokers, and drinkers in their social networks. Homophily within the networks also indicates that gamblers tend to be closer with other gamblers. This homophily may serve to reinforce addictive behaviors, and may suggest avenues for future study or intervention. PMID:23072641

  3. Egocentric social network analysis of pathological gambling.

    Science.gov (United States)

    Meisel, Matthew K; Clifton, Allan D; Mackillop, James; Miller, Joshua D; Campbell, W Keith; Goodie, Adam S

    2013-03-01

    To apply social network analysis (SNA) to investigate whether frequency and severity of gambling problems were associated with different network characteristics among friends, family and co-workers is an innovative way to look at relationships among individuals; the current study was the first, to our knowledge, to apply SNA to gambling behaviors. Egocentric social network analysis was used to characterize formally the relationships between social network characteristics and gambling pathology. Laboratory-based questionnaire and interview administration. Forty frequent gamblers (22 non-pathological gamblers, 18 pathological gamblers) were recruited from the community. The SNA revealed significant social network compositional differences between the two groups: pathological gamblers (PGs) had more gamblers, smokers and drinkers in their social networks than did non-pathological gamblers (NPGs). PGs had more individuals in their network with whom they personally gambled, smoked and drank than those with who were NPG. Network ties were closer to individuals in their networks who gambled, smoked and drank more frequently. Associations between gambling severity and structural network characteristics were not significant. Pathological gambling is associated with compositional but not structural differences in social networks. Pathological gamblers differ from non-pathological gamblers in the number of gamblers, smokers and drinkers in their social networks. Homophily within the networks also indicates that gamblers tend to be closer with other gamblers. This homophily may serve to reinforce addictive behaviors, and may suggest avenues for future study or intervention. © 2012 The Authors, Addiction © 2012 Society for the Study of Addiction.

  4. A method for identifying hierarchical sub-networks / modules and weighting network links based on their similarity in sub-network / module affiliation

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2016-06-01

    Full Text Available Some networks, including biological networks, consist of hierarchical sub-networks / modules. Based on my previous study, in present study a method for both identifying hierarchical sub-networks / modules and weighting network links is proposed. It is based on the cluster analysis in which between-node similarity in sets of adjacency nodes is used. Two matrices, linkWeightMat and linkClusterIDs, are achieved by using the algorithm. Two links with both the same weight in linkWeightMat and the same cluster ID in linkClusterIDs belong to the same sub-network / module. Two links with the same weight in linkWeightMat but different cluster IDs in linkClusterIDs belong to two sub-networks / modules at the same hirarchical level. However, a link with an unique cluster ID in linkClusterIDs does not belong to any sub-networks / modules. A sub-network / module of the greater weight is the more connected sub-network / modules. Matlab codes of the algorithm are presented.

  5. Will Learning Social Inclusion Assist Rural Networks

    Science.gov (United States)

    Marchant, Jillian

    2013-01-01

    Current research on social networks in some rural communities reports continuing demise despite efforts to build resilient communities. Several factors are identified as contributing to social decline including globalisation and rural social characteristics. Particular rural social characteristics, such as strong social bonds among members of…

  6. Hierarchical organization of functional connectivity in the mouse brain: a complex network approach.

    Science.gov (United States)

    Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano

    2016-08-18

    This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.

  7. Social networks and human development / Redes sociales y desarrollo humano

    Directory of Open Access Journals (Sweden)

    Sara Gallego Trijueque

    2011-10-01

    Full Text Available The aim of this work is a brief introduction to the concept of social networks and their importance in society. Social networks have been responsible over the centuries to preserve community values, in addition to being facilitators of social interaction in human development processes, through communication and relationships between individuals.

  8. Social Media and Social Networking Applications for Teaching and Learning

    Science.gov (United States)

    Yeo, Michelle Mei Ling

    2014-01-01

    This paper aims to better understand the experiences of the youth and the educators with the tapping of social media like YouTube videos and the social networking application of Facebook for teaching and learning. This paper is interested in appropriating the benefits of leveraging of social media and networking applications like YouTube and…

  9. Social Rewards and Social Networks in the Human Brain.

    Science.gov (United States)

    Fareri, Dominic S; Delgado, Mauricio R

    2014-08-01

    The rapid development of social media and social networking sites in human society within the past decade has brought about an increased focus on the value of social relationships and being connected with others. Research suggests that we pursue socially valued or rewarding outcomes-approval, acceptance, reciprocity-as a means toward learning about others and fulfilling social needs of forming meaningful relationships. Focusing largely on recent advances in the human neuroimaging literature, we review findings highlighting the neural circuitry and processes that underlie pursuit of valued rewarding outcomes across non-social and social domains. We additionally discuss emerging human neuroimaging evidence supporting the idea that social rewards provide a gateway to establishing relationships and forming social networks. Characterizing the link between social network, brain, and behavior can potentially identify contributing factors to maladaptive influences on decision making within social situations. © The Author(s) 2014.

  10. Spatially Distributed Social Complex Networks

    Directory of Open Access Journals (Sweden)

    Gerald F. Frasco

    2014-01-01

    Full Text Available We propose a bare-bones stochastic model that takes into account both the geographical distribution of people within a country and their complex network of connections. The model, which is designed to give rise to a scale-free network of social connections and to visually resemble the geographical spread seen in satellite pictures of the Earth at night, gives rise to a power-law distribution for the ranking of cities by population size (but for the largest cities and reflects the notion that highly connected individuals tend to live in highly populated areas. It also yields some interesting insights regarding Gibrat’s law for the rates of city growth (by population size, in partial support of the findings in a recent analysis of real data [Rozenfeld et al., Proc. Natl. Acad. Sci. U.S.A. 105, 18702 (2008.]. The model produces a nontrivial relation between city population and city population density and a superlinear relationship between social connectivity and city population, both of which seem quite in line with real data.

  11. Spatially Distributed Social Complex Networks

    Science.gov (United States)

    Frasco, Gerald F.; Sun, Jie; Rozenfeld, Hernán D.; ben-Avraham, Daniel

    2014-01-01

    We propose a bare-bones stochastic model that takes into account both the geographical distribution of people within a country and their complex network of connections. The model, which is designed to give rise to a scale-free network of social connections and to visually resemble the geographical spread seen in satellite pictures of the Earth at night, gives rise to a power-law distribution for the ranking of cities by population size (but for the largest cities) and reflects the notion that highly connected individuals tend to live in highly populated areas. It also yields some interesting insights regarding Gibrat's law for the rates of city growth (by population size), in partial support of the findings in a recent analysis of real data [Rozenfeld et al., Proc. Natl. Acad. Sci. U.S.A. 105, 18702 (2008).]. The model produces a nontrivial relation between city population and city population density and a superlinear relationship between social connectivity and city population, both of which seem quite in line with real data.

  12. Performance Analysis of Hierarchical Group Key Management Integrated with Adaptive Intrusion Detection in Mobile ad hoc Networks

    Science.gov (United States)

    2016-04-05

    applications in wireless networks such as military battlefields, emergency response, mobile commerce , online gaming, and collaborative work are based on the...www.elsevier.com/locate/peva Performance analysis of hierarchical group key management integrated with adaptive intrusion detection in mobile ad hoc...Accepted 19 September 2010 Available online 26 September 2010 Keywords: Mobile ad hoc networks Intrusion detection Group communication systems Group

  13. Social networks in cardiovascular disease management.

    Science.gov (United States)

    Shaya, Fadia T; Yan, Xia; Farshid, Maryam; Barakat, Samer; Jung, Miah; Low, Sara; Fedder, Donald

    2010-12-01

    Cardiovascular disease remains the leading cause of death in the USA. Social networks have a positive association with obesity, smoking cessation and weight loss. This article summarizes studies evaluating the impact of social networks on the management of cardiovascular disease. The 35 studies included in the article describe the impact of social networks on a decreased incidence of cardiovascular disease, depression and mortality. In addition, having a large-sized social network is also associated with better outcomes and improved health. The role of pharmacists is beginning to play an important role in the patient-centered medical home, which needs to be incorporated into social networks. The patient-centered medical home can serve as an adaptive source for social network evolvement.

  14. Hierarchical thinking in network biology: the unbiased modularization of biochemical networks.

    Science.gov (United States)

    Papin, Jason A; Reed, Jennifer L; Palsson, Bernhard O

    2004-12-01

    As reconstructed biochemical reaction networks continue to grow in size and scope, there is a growing need to describe the functional modules within them. Such modules facilitate the study of biological processes by deconstructing complex biological networks into conceptually simple entities. The definition of network modules is often based on intuitive reasoning. As an alternative, methods are being developed for defining biochemical network modules in an unbiased fashion. These unbiased network modules are mathematically derived from the structure of the whole network under consideration.

  15. Networking for philanthropy: increasing volunteer behavior via social networking sites.

    Science.gov (United States)

    Kim, Yoojung; Lee, Wei-Na

    2014-03-01

    Social networking sites (SNSs) provide a unique social venue to engage the young generation in philanthropy through their networking capabilities. An integrated model that incorporates social capital into the Theory of Reasoned Action is developed to explain volunteer behavior through social networks. As expected, volunteer behavior was predicted by volunteer intention, which was influenced by attitudes and subjective norms. In addition, social capital, an outcome of the extensive use of SNSs, was as an important driver of users' attitude and subjective norms toward volunteering via SNSs.

  16. Social Networking Sites: A premise on enhancement

    OpenAIRE

    MANINDERPAL SINGH SAINI; GYEWON MOON

    2013-01-01

    This article address five constructs that are paramount toward continued evolution of social networking sites (SNS`s) they include, - stabilisation, visual, language, security and flexibility. These constructs add to our proposed framework. Firmly grounded research on social networking sites and literature, we propose that user feedback, is the critical component that stimulates the development and growth of social networking sites online. We offer a framework that can aid new and current soc...

  17. PRIVACY PROTECTION PROBLEMS IN SOCIAL NETWORKS

    OpenAIRE

    OKUR, M. Cudi

    2011-01-01

    Protecting privacy has become a major concern for most social network users because of increased difficulties of controlling the online data. This article presents an assessment of the common privacy related risks of social networking sites. Open and hidden privacy risks of active and passive online profiles are examined and increasing share of social networking in these phenomena is discussed. Inadequacy of available legal and institutional protection is demonstrated and the effectiveness of...

  18. Social Networks and Political Parties in Chile

    OpenAIRE

    Adler Lomnitz, Larissa

    2002-01-01

    This paper describes the origin and evolution of two Chilean political parties (the Radical Party and the Christian Democrat Party) through the analysis of the social networks that originated and composed them. The aim of this study is to propose a model of national political cultures on the basis of the structure of social networks related to power and of the symbol system, which legitimizes it. The structure of social networks, horizontal and vertical, are based on reciprocal or redistribut...

  19. The Strategic Paradox of Social Networks

    Science.gov (United States)

    2011-03-18

    United States claimed to have met online.9 And in 2010, Facebook claimed over 500 million users, which would make the social networking service the...service culture, or occupational specialty. One drawback with social networks concerns the protection of individual privacy. Facebook , for...St ra te gy R es ea rc h Pr oj ec t THE STRATEGIC PARADOX OF SOCIAL NETWORKS BY COLONEL ROBERT COTE United States Marine Corps

  20. Hierarchical structures of correlations networks among Turkey’s exports and imports by currencies

    Science.gov (United States)

    Kocakaplan, Yusuf; Deviren, Bayram; Keskin, Mustafa

    2012-12-01

    We have examined the hierarchical structures of correlations networks among Turkey’s exports and imports by currencies for the 1996-2010 periods, using the concept of a minimal spanning tree (MST) and hierarchical tree (HT) which depend on the concept of ultrametricity. These trees are useful tools for understanding and detecting the global structure, taxonomy and hierarchy in financial markets. We derived a hierarchical organization and build the MSTs and HTs during the 1996-2001 and 2002-2010 periods. The reason for studying two different sub-periods, namely 1996-2001 and 2002-2010, is that the Euro (EUR) came into use in 2001, and some countries have made their exports and imports with Turkey via the EUR since 2002, and in order to test various time-windows and observe temporal evolution. We have carried out bootstrap analysis to associate a value of the statistical reliability to the links of the MSTs and HTs. We have also used the average linkage cluster analysis (ALCA) to observe the cluster structure more clearly. Moreover, we have obtained the bidimensional minimal spanning tree (BMST) due to economic trade being a bidimensional problem. From the structural topologies of these trees, we have identified different clusters of currencies according to their proximity and economic ties. Our results show that some currencies are more important within the network, due to a tighter connection with other currencies. We have also found that the obtained currencies play a key role for Turkey’s exports and imports and have important implications for the design of portfolio and investment strategies.

  1. Optimization of workflow scheduling in Utility Management System with hierarchical neural network

    Directory of Open Access Journals (Sweden)

    Srdjan Vukmirovic

    2011-08-01

    Full Text Available Grid computing could be the future computing paradigm for enterprise applications, one of its benefits being that it can be used for executing large scale applications. Utility Management Systems execute very large numbers of workflows with very high resource requirements. This paper proposes architecture for a new scheduling mechanism that dynamically executes a scheduling algorithm using feedback about the current status Grid nodes. Two Artificial Neural Networks were created in order to solve the scheduling problem. A case study is created for the Meter Data Management system with measurements from the Smart Metering system for the city of Novi Sad, Serbia. Performance tests show that significant improvement of overall execution time can be achieved by Hierarchical Artificial Neural Networks.

  2. Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

    Science.gov (United States)

    Zhu, Aichun; Wang, Tian; Snoussi, Hichem

    2018-03-01

    This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

  3. Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

    Directory of Open Access Journals (Sweden)

    Aichun Zhu

    2018-03-01

    Full Text Available This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN. Firstly, a Relative Mixture Deformable Model (RMDM is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

  4. SMR-Based Adaptive Mobility Management Scheme in Hierarchical SIP Networks

    Directory of Open Access Journals (Sweden)

    KwangHee Choi

    2014-10-01

    Full Text Available In hierarchical SIP networks, paging is performed to reduce location update signaling cost for mobility management. However, the cost efficiency largely depends on each mobile node’s session-to-mobility-ratio (SMR, which is defined as a ratio of the session arrival rate to the movement rate. In this paper, we propose the adaptive mobility management scheme that can determine the policy regarding to each mobile node’s SMR. Each mobile node determines whether the paging is applied or not after comparing its SMR with the threshold. In other words, the paging is applied to a mobile node when a mobile node’s SMR is less than the threshold. Therefore, the proposed scheme provides a way to minimize signaling costs according to each mobile node’s SMR. We find out the optimal threshold through performance analysis, and show that the proposed scheme can reduce signaling cost than the existing SIP and paging schemes in hierarchical SIP networks.

  5. Social network analysis community detection and evolution

    CERN Document Server

    Missaoui, Rokia

    2015-01-01

    This book is devoted to recent progress in social network analysis with a high focus on community detection and evolution. The eleven chapters cover the identification of cohesive groups, core components and key players either in static or dynamic networks of different kinds and levels of heterogeneity. Other important topics in social network analysis such as influential detection and maximization, information propagation, user behavior analysis, as well as network modeling and visualization are also presented. Many studies are validated through real social networks such as Twitter. This edit

  6. Privacy Breach Analysis in Social Networks

    Science.gov (United States)

    Nagle, Frank

    This chapter addresses various aspects of analyzing privacy breaches in social networks. We first review literature that defines three types of privacy breaches in social networks: interactive, active, and passive. We then survey the various network anonymization schemes that have been constructed to address these privacy breaches. After exploring these breaches and anonymization schemes, we evaluate a measure for determining the level of anonymity inherent in a network graph based on its topological structure. Finally, we close by emphasizing the difficulty of anonymizing social network data while maintaining usability for research purposes and offering areas for future work.

  7. Data mining for social network data

    CERN Document Server

    Memon, Nasrullah; Hicks, David L; Chen, Hsinchun

    2010-01-01

    Driven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved to the forefront of information science. This proposed Special Issue on ""Data Mining for Social Network Data"" will present a broad range of recent studies in social networking analysis. It will focus on emerging trends and needs in discovery and analysis of communities, solitary and social activities, and activities in open fora, and commercial sites as well. It will also look at network modeling, infrastructure construction, dynamic growth and evolution

  8. Information and influence propagation in social networks

    CERN Document Server

    Chen, Wei; Lakshmanan, Laks V S

    2013-01-01

    Research on social networks has exploded over the last decade. To a large extent, this has been fueled by the spectacular growth of social media and online social networking sites, which continue growing at a very fast pace, as well as by the increasing availability of very large social network datasets for purposes of research. A rich body of this research has been devoted to the analysis of the propagation of information, influence, innovations, infections, practices and customs through networks. Can we build models to explain the way these propagations occur? How can we validate our models

  9. Social relations: network, support and relational strain

    DEFF Research Database (Denmark)

    Due, P; Holstein, B; Lund, Rikke

    1999-01-01

    We introduce a conceptual framework with social relations as the main concept and the structure and the function of social relations as subconcepts. The structure of social relations covers aspects of formal relations and social network. The function of social relations covers social support......,011. The postal questionnaires were answered by a random sample in each of the age groups. The results show marked age and gender differences in both the structure and the function of social relations. The social network, measured as weekly contacts, weakens with age and so does instrumental support. Emotional...... support is unrelated to this decline in contact frequency and appears to be at the same level for younger and older individuals. Relational strain, measured as conflicts, declines with age for all kinds of social relations. The weakening of the social network with age does not seem to affect the level...

  10. Animal welfare: a social networks perspective.

    Science.gov (United States)

    Kleinhappel, Tanja K; John, Elizabeth A; Pike, Thomas W; Wilkinson, Anna; Burman, Oliver H P

    2016-01-01

    Social network theory provides a useful tool to study complex social relationships in animals. The possibility to look beyond dyadic interactions by considering whole networks of social relationships allows researchers the opportunity to study social groups in more natural ways. As such, network-based analyses provide an informative way to investigate the factors influencing the social environment of group-living animals, and so has direct application to animal welfare. For example, animal groups in captivity are frequently disrupted by separations, reintroductions and/or mixing with unfamiliar individuals and this can lead to social stress and associated aggression. Social network analysis ofanimal groups can help identify the underlying causes of these socially-derived animal welfare concerns. In this review we discuss how this approach can be applied, and how it could be used to identify potential interventions and solutions in the area of animal welfare.

  11. Latent Space Approaches to Social Network Analysis

    National Research Council Canada - National Science Library

    Hoff, Peter D; Raftery, Adrian E; Handcock, Mark S

    2001-01-01

    .... In studies of social networks, recent emphasis has been placed on random graph models where the nodes usually represent individual social actors and the edges represent the presence of a specified...

  12. Opinion evolution in different social acquaintance networks.

    Science.gov (United States)

    Chen, Xi; Zhang, Xiao; Wu, Zhan; Wang, Hongwei; Wang, Guohua; Li, Wei

    2017-11-01

    Social acquaintance networks influenced by social culture and social policy have a great impact on public opinion evolution in daily life. Based on the differences between socio-culture and social policy, three different social acquaintance networks (kinship-priority acquaintance network, independence-priority acquaintance network, and hybrid acquaintance network) incorporating heredity proportion p h and variation proportion p v are proposed in this paper. Numerical experiments are conducted to investigate network topology and different phenomena during opinion evolution, using the Deffuant model. We found that in kinship-priority acquaintance networks, similar to the Chinese traditional acquaintance networks, opinions always achieve fragmentation, resulting in the formation of multiple large clusters and many small clusters due to the fact that individuals believe more in their relatives and live in a relatively closed environment. In independence-priority acquaintance networks, similar to Western acquaintance networks, the results are similar to those in the kinship-priority acquaintance network. In hybrid acquaintance networks, similar to the Chinese modern acquaintance networks, only a few clusters are formed indicating that in modern China, opinions are more likely to reach consensus on a large scale. These results are similar to the opinion evolution phenomena in modern society, proving the rationality and applicability of network models combined with social culture and policy. We also found a threshold curve p v +2p h =2.05 in the results for the final opinion clusters and evolution time. Above the threshold curve, opinions could easily reach consensus. Based on the above experimental results, a culture-policy-driven mechanism for the opinion dynamic is worth promoting in this paper, that is, opinion dynamics can be driven by different social cultures and policies through the influence of heredity and variation in interpersonal relationship networks. This

  13. Opinion evolution in different social acquaintance networks

    Science.gov (United States)

    Chen, Xi; Zhang, Xiao; Wu, Zhan; Wang, Hongwei; Wang, Guohua; Li, Wei

    2017-11-01

    Social acquaintance networks influenced by social culture and social policy have a great impact on public opinion evolution in daily life. Based on the differences between socio-culture and social policy, three different social acquaintance networks (kinship-priority acquaintance network, independence-priority acquaintance network, and hybrid acquaintance network) incorporating heredity proportion ph and variation proportion pv are proposed in this paper. Numerical experiments are conducted to investigate network topology and different phenomena during opinion evolution, using the Deffuant model. We found that in kinship-priority acquaintance networks, similar to the Chinese traditional acquaintance networks, opinions always achieve fragmentation, resulting in the formation of multiple large clusters and many small clusters due to the fact that individuals believe more in their relatives and live in a relatively closed environment. In independence-priority acquaintance networks, similar to Western acquaintance networks, the results are similar to those in the kinship-priority acquaintance network. In hybrid acquaintance networks, similar to the Chinese modern acquaintance networks, only a few clusters are formed indicating that in modern China, opinions are more likely to reach consensus on a large scale. These results are similar to the opinion evolution phenomena in modern society, proving the rationality and applicability of network models combined with social culture and policy. We also found a threshold curve pv+2 ph=2.05 in the results for the final opinion clusters and evolution time. Above the threshold curve, opinions could easily reach consensus. Based on the above experimental results, a culture-policy-driven mechanism for the opinion dynamic is worth promoting in this paper, that is, opinion dynamics can be driven by different social cultures and policies through the influence of heredity and variation in interpersonal relationship networks. This

  14. Social networking and privacy attitudes among

    OpenAIRE

    Kristen A. Carruth; Harvey J. Ginsburg

    2014-01-01

    Daily use of social networking sites (SNS) such as Facebook has become routine for millions of Internet users. Facebook is currently still the most popular social media site. Social networking has been rapidly adopted by societies around the world. In particular, social media like Facebook provide sites where users can personalize a profile with their information, pictures, and videos that can be shared with other users. This information can be used in ways that may violate users’ privacy ...

  15. Social networks, social satisfaction and place attachment in the neighborhood

    NARCIS (Netherlands)

    Weijs - Perrée, M.; van den Berg, P.E.W.; Arentze, T.A.; Kemperman, A.D.A.M.

    2017-01-01

    Feeling socially integrated and being satisfied with one’s social life are important indicators for happiness and well-being of individuals and for the strength of local communities. The effect of the living environment on social networks and the importance of local social contacts in the

  16. Social networks and links to isolation and loneliness among elderly HCBS clients.

    Science.gov (United States)

    Medvene, Louis J; Nilsen, Kari M; Smith, Rachel; Ofei-Dodoo, Samuel; DiLollo, Anthony; Webster, Noah; Graham, Annette; Nance, Anita

    2016-01-01

    The purpose of this study was to explore the network types of HCBS clients based on the structural characteristics of their social networks. We also examined how the network types were associated with social isolation, relationship quality and loneliness. Forty personal interviews were carried out with HCBS clients to assess the structure of their social networks as indicated by frequency of contact with children, friends, family and participation in religious and community organizations. Hierarchical cluster analysis was conducted to identify network types. Four network types were found including: family (n = 16), diverse (n = 8), restricted (n = 8) and religious (n = 7). Family members comprised almost half of participants' social networks, and friends comprised less than one-third. Clients embedded in family, diverse and religious networks had significantly more positive relationships than clients embedded in restricted networks. Clients embedded in restricted networks had significantly higher social isolation scores and were lonelier than clients in diverse and family networks. The findings suggest that HCBS clients' isolation and loneliness are linked to the types of social networks in which they are embedded. The findings also suggest that clients embedded in restricted networks are at high risk for negative outcomes.

  17. Mobile Social Network in a Cultural Context

    DEFF Research Database (Denmark)

    Liu, Jun

    2010-01-01

    , and mobile phone rumours, this study observes that mobile social networks are a way that Chinese people cultivate, maintain and strengthen their guanxi networks. Embedding the reliability of guanxi, the message spreading via mobile communication always enjoys high credibility, while mutual obligation...... of mobile social network in China therefore emanate not only from Information and Communication Technologies, but also from the socio-cultural source - guanxi - deeply rooted in Chinese society.......the chapter “Mobile Social Network in a Cultural Context” examines the guanxi-embedded mobile social network in China. By focusing on three concrete case studies with 56 in-depth interviews, including New Year text message greetings, mobile social networks for job allocations among migrant workers...

  18. Mobile social networking an innovative approach

    CERN Document Server

    Zhang, Daqing

    2014-01-01

    The use of contextually aware, pervasive, distributed computing, and sensor networks to bridge the gap between the physical and online worlds is the basis of mobile social networking. This book shows how applications can be built to provide mobile social networking, the research issues that need to be solved to enable this vision, and how mobile social networking can be used to provide computational intelligence that will improve daily life. With contributions from the fields of sociology, computer science, human-computer interaction and design, this book demonstrates how mobile social networks can be inferred from users' physical interactions both with the environment and with others, as well as how users behave around them and how their behavior differs on mobile vs. traditional online social networks.

  19. Social network in patient safety: Social media visibility

    Directory of Open Access Journals (Sweden)

    Azucena Santillán García

    2011-11-01

    Full Text Available Internet social network (social media is a powerful communication tool, and its use is expanding significantly. This paper seeks to know the current state of visibility in online social networks of active citizen talking about patient safety. This is an observational cross-sectional study whose target population is the websites Facebook, Twitter and Tuenti in Spain. By three consecutive cuts social profiles were found using the searching terms “seguridad+paciente” and “safety+patient”. There were found 5 profiles on Facebook that met the search criteria, 6 on Twitter and none were found on Tuenti. It is concluded that although there is evidence of the rise of social networking, citizen network involved in patient safety appears not to be significantly represented within the social networks examined.

  20. Social network and lifestyle in Danish adults

    DEFF Research Database (Denmark)

    Osler, Merete

    1995-01-01

    Analyzed associations between 2,987 adults' social networks and lifestyles in terms of leisure activity, smoking, and the intake of vegetables. Compared with socially integrated men, those with few social contacts or little social support were more often inactive during leisure time and did not e...... health related behaviors. (PsycINFO Database Record (c) 2012 APA, all rights reserved)...

  1. Link prediction in multiplex online social networks

    Science.gov (United States)

    Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin; Perc, Matjaž

    2017-02-01

    Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.

  2. Social network analysis and supply chain management

    Directory of Open Access Journals (Sweden)

    Raúl Rodríguez Rodríguez

    2016-01-01

    Full Text Available This paper deals with social network analysis and how it could be integrated within supply chain management from a decision-making point of view. Even though the benefits of using social analysis have are widely accepted at both academic and industry/services context, there is still a lack of solid frameworks that allow decision-makers to connect the usage and obtained results of social network analysis – mainly both information and knowledge flows and derived results- with supply chain management objectives and goals. This paper gives an overview of social network analysis, the main social network analysis metrics, supply chain performance and, finally, it identifies how future frameworks could close the gap and link the results of social network analysis with the supply chain management decision-making processes.

  3. Fundamental structures of dynamic social networks

    DEFF Research Database (Denmark)

    Sekara, Vedran; Stopczynski, Arkadiusz; Jørgensen, Sune Lehmann

    2016-01-01

    Social systems are in a constant state of flux, with dynamics spanning from minute-by-minute changes to patterns present on the timescale of years. Accurate models of social dynamics are important for understanding the spreading of influence or diseases, formation of friendships...... and their interactions in the network of real-world person-to-person proximity measured via Bluetooth, as well as their telecommunication networks, online social media contacts, geolocation, and demographic data. These high-resolution data allow us to observe social groups directly, rendering community detection......, and the productivity of teams. Although there has been much progress on understanding complex networks over the past decade, little is known about the regularities governing the microdynamics of social networks. Here, we explore the dynamic social network of a densely-connected population of ∼1,000 individuals...

  4. A Comprehensive Survey on Hierarchical-Based Routing Protocols for Mobile Wireless Sensor Networks: Review, Taxonomy, and Future Directions

    Directory of Open Access Journals (Sweden)

    Nabil Sabor

    2017-01-01

    Full Text Available Introducing mobility to Wireless Sensor Networks (WSNs puts new challenges particularly in designing of routing protocols. Mobility can be applied to the sensor nodes and/or the sink node in the network. Many routing protocols have been developed to support the mobility of WSNs. These protocols are divided depending on the routing structure into hierarchical-based, flat-based, and location-based routing protocols. However, the hierarchical-based routing protocols outperform the other routing types in saving energy, scalability, and extending lifetime of Mobile WSNs (MWSNs. Selecting an appropriate hierarchical routing protocol for specific applications is an important and difficult task. Therefore, this paper focuses on reviewing some of the recently hierarchical-based routing protocols that are developed in the last five years for MWSNs. This survey divides the hierarchical-based routing protocols into two broad groups, namely, classical-based and optimized-based routing protocols. Also, we present a detailed classification of the reviewed protocols according to the routing approach, control manner, mobile element, mobility pattern, network architecture, clustering attributes, protocol operation, path establishment, communication paradigm, energy model, protocol objectives, and applications. Moreover, a comparison between the reviewed protocols is investigated in this survey depending on delay, network size, energy-efficiency, and scalability while mentioning the advantages and drawbacks of each protocol. Finally, we summarize and conclude the paper with future directions.

  5. Heads First: Visual Aftereffects Reveal Hierarchical Integration of Cues to Social Attention.

    Directory of Open Access Journals (Sweden)

    Sarah Cooney

    Full Text Available Determining where another person is attending is an important skill for social interaction that relies on various visual cues, including the turning direction of the head and body. This study reports a novel high-level visual aftereffect that addresses the important question of how these sources of information are combined in gauging social attention. We show that adapting to images of heads turned 25° to the right or left produces a perceptual bias in judging the turning direction of subsequently presented bodies. In contrast, little to no change in the judgment of head orientation occurs after adapting to extremely oriented bodies. The unidirectional nature of the aftereffect suggests that cues from the human body signaling social attention are combined in a hierarchical fashion and is consistent with evidence from single-cell recording studies in nonhuman primates showing that information about head orientation can override information about body posture when both are visible.

  6. Science, Society, and Social Networking

    Science.gov (United States)

    White, K. S.; Lohwater, T.

    2009-12-01

    The increased use of social networking is changing the way that scientific societies interact with their members and others. The American Association for the Advancement of Science (AAAS) uses a variety of online networks to engage its members and the broader scientific community. AAAS members and non-members can interact with AAAS staff and each other on AAAS sites on Facebook, YouTube, and Twitter, as well as blogs and forums on the AAAS website (www.aaas.org). These tools allow scientists to more readily become engaged in policy by providing information on current science policy topics as well as methods of involvement. For example, members and the public can comment on policy-relevant stories from Science magazine’s ScienceInsider blog, download a weekly policy podcast, receive a weekly email update of policy issues affecting the scientific community, or watch a congressional hearing from their computer. AAAS resource websites and outreach programs, including Communicating Science (www.aaas.org/communicatingscience), Working with Congress (www.aaas.org/spp/cstc/) and Science Careers (http://sciencecareers.sciencemag.org) also provide tools for scientists to become more personally engaged in communicating their findings and involved in the policy process.

  7. Trust transitivity in social networks.

    Directory of Open Access Journals (Sweden)

    Oliver Richters

    Full Text Available Non-centralized recommendation-based decision making is a central feature of several social and technological processes, such as market dynamics, peer-to-peer file-sharing and the web of trust of digital certification. We investigate the properties of trust propagation on networks, based on a simple metric of trust transitivity. We investigate analytically the percolation properties of trust transitivity in random networks with arbitrary in/out-degree distributions, and compare with numerical realizations. We find that the existence of a non-zero fraction of absolute trust (i.e. entirely confident trust is a requirement for the viability of global trust propagation in large systems: The average pair-wise trust is marked by a discontinuous transition at a specific fraction of absolute trust, below which it vanishes. Furthermore, we perform an extensive analysis of the Pretty Good Privacy (PGP web of trust, in view of the concepts introduced. We compare different scenarios of trust distribution: community- and authority-centered. We find that these scenarios lead to sharply different patterns of trust propagation, due to the segregation of authority hubs and densely-connected communities. While the authority-centered scenario is more efficient, and leads to higher average trust values, it favours weakly-connected "fringe" nodes, which are directly trusted by authorities. The community-centered scheme, on the other hand, favours nodes with intermediate in/out-degrees, in detriment of the authorities and its "fringe" peers.

  8. Trust Transitivity in Social Networks

    Science.gov (United States)

    Richters, Oliver; Peixoto, Tiago P.

    2011-01-01

    Non-centralized recommendation-based decision making is a central feature of several social and technological processes, such as market dynamics, peer-to-peer file-sharing and the web of trust of digital certification. We investigate the properties of trust propagation on networks, based on a simple metric of trust transitivity. We investigate analytically the percolation properties of trust transitivity in random networks with arbitrary in/out-degree distributions, and compare with numerical realizations. We find that the existence of a non-zero fraction of absolute trust (i.e. entirely confident trust) is a requirement for the viability of global trust propagation in large systems: The average pair-wise trust is marked by a discontinuous transition at a specific fraction of absolute trust, below which it vanishes. Furthermore, we perform an extensive analysis of the Pretty Good Privacy (PGP) web of trust, in view of the concepts introduced. We compare different scenarios of trust distribution: community- and authority-centered. We find that these scenarios lead to sharply different patterns of trust propagation, due to the segregation of authority hubs and densely-connected communities. While the authority-centered scenario is more efficient, and leads to higher average trust values, it favours weakly-connected “fringe” nodes, which are directly trusted by authorities. The community-centered scheme, on the other hand, favours nodes with intermediate in/out-degrees, in detriment of the authorities and its “fringe” peers. PMID:21483683

  9. Kinship, family and social network

    Directory of Open Access Journals (Sweden)

    2000-12-01

    Full Text Available There is considerable overlap between Le Play's mid-eighteenth-century household model map and the regional TFR map of central-southern Europe in the 1980s. The author examines the overall structure of relationships involved in Le Play's typology and observes that both the stem-family and the unstable family area in the Southern Europe are marked by a small, close-knit network of strong ties, with kinship predominance. Vice versa, the social support hinges upon a network of kin in the stem-family area, upon an alliance among different kindred units in the unstable Mediterranean area. All this leads to formulating a hypothesis of a tri-partite model for Western European relationship models. How can we explain the relationship between family predominance as anthropological embedding and family collapse as demographic reaction? The author reconsiders this question in the light of Festinger's cognitive dissonance theory and Elder's 'principle of accentuation': different, regionally rooted, family and kinship patterns "react" in contact with an appropriate reagent, such as the macro-process of modernisation, generating different patterns of today's demographic behaviour.

  10. Spectral Analysis of Rich Network Topology in Social Networks

    Science.gov (United States)

    Wu, Leting

    2013-01-01

    Social networks have received much attention these days. Researchers have developed different methods to study the structure and characteristics of the network topology. Our focus is on spectral analysis of the adjacency matrix of the underlying network. Recent work showed good properties in the adjacency spectral space but there are few…

  11. Corporate Social Responsibility in Online Social Networks

    DEFF Research Database (Denmark)

    Horn, Christian; Brem, Alexander; Wölfl, S.

    2014-01-01

    Considering growing public awareness of social, ethical and ecological responsibility, companies have constantly been increasing their efforts in CSR communications. Social Media as tools of brand communication receive increasing attention and it is expected that the marketing sector...

  12. A Hierarchical Poisson Log-Normal Model for Network Inference from RNA Sequencing Data

    Science.gov (United States)

    Gallopin, Mélina; Rau, Andrea; Jaffrézic, Florence

    2013-01-01

    Gene network inference from transcriptomic data is an important methodological challenge and a key aspect of systems biology. Although several methods have been proposed to infer networks from microarray data, there is a need for inference methods able to model RNA-seq data, which are count-based and highly variable. In this work we propose a hierarchical Poisson log-normal model with a Lasso penalty to infer gene networks from RNA-seq data; this model has the advantage of directly modelling discrete data and accounting for inter-sample variance larger than the sample mean. Using real microRNA-seq data from breast cancer tumors and simulations, we compare this method to a regularized Gaussian graphical model on log-transformed data, and a Poisson log-linear graphical model with a Lasso penalty on power-transformed data. For data simulated with large inter-sample dispersion, the proposed model performs better than the other methods in terms of sensitivity, specificity and area under the ROC curve. These results show the necessity of methods specifically designed for gene network inference from RNA-seq data. PMID:24147011

  13. Nonlinear model of epidemic spreading in a complex social network.

    Science.gov (United States)

    Kosiński, Robert A; Grabowski, A

    2007-10-01

    The epidemic spreading in a human society is a complex process, which can be described on the basis of a nonlinear mathematical model. In such an approach the complex and hierarchical structure of social network (which has implications for the spreading of pathogens and can be treated as a complex network), can be taken into account. In our model each individual has one of the four permitted states: susceptible, infected, infective, unsusceptible or dead. This refers to the SEIR model used in epidemiology. The state of an individual changes in time, depending on the previous state and the interactions with other individuals. The description of the interpersonal contacts is based on the experimental observations of the social relations in the community. It includes spatial localization of the individuals and hierarchical structure of interpersonal interactions. Numerical simulations were performed for different types of epidemics, giving the progress of a spreading process and typical relationships (e.g. range of epidemic in time, the epidemic curve). The spreading process has a complex and spatially chaotic character. The time dependence of the number of infective individuals shows the nonlinear character of the spreading process. We investigate the influence of the preventive vaccinations on the spreading process. In particular, for a critical value of preventively vaccinated individuals the percolation threshold is observed and the epidemic is suppressed.

  14. Social Software: Participants' Experience Using Social Networking for Learning

    Science.gov (United States)

    Batchelder, Cecil W.

    2010-01-01

    Social networking tools used in learning provides instructional design with tools for transformative change in education. This study focused on defining the meanings and essences of social networking through the lived common experiences of 7 college students. The problem of the study was a lack of learner voice in understanding the value of social…

  15. Going Social: The Impact of Social Networking in Promoting Education

    Science.gov (United States)

    Jain, Neelesh Kumar; Verma, Ashish; Verma, Rama Shankar; Tiwari, Prashant

    2012-01-01

    The growth and the popularity of the Social networks has a high impact on the development of the students in the field of Personality, Attitudes, Knowledge and on its whole academic performance in classroom and society. This paper envisage on the impact of Social Network on Education and Training of the students.

  16. Mining of the social network extraction

    Science.gov (United States)

    Nasution, M. K. M.; Hardi, M.; Syah, R.

    2017-01-01

    The use of Web as social media is steadily gaining ground in the study of social actor behaviour. However, information in Web can be interpreted in accordance with the ability of the method such as superficial methods for extracting social networks. Each method however has features and drawbacks: it cannot reveal the behaviour of social actors, but it has the hidden information about them. Therefore, this paper aims to reveal such information in the social networks mining. Social behaviour could be expressed through a set of words extracted from the list of snippets.

  17. Spreading in online social networks: the role of social reinforcement.

    Science.gov (United States)

    Zheng, Muhua; Lü, Linyuan; Zhao, Ming

    2013-07-01

    Some epidemic spreading models are usually applied to analyze the propagation of opinions or news. However, the dynamics of epidemic spreading and information or behavior spreading are essentially different in many aspects. Centola's experiments [Science 329, 1194 (2010)] on behavior spreading in online social networks showed that the spreading is faster and broader in regular networks than in random networks. This result contradicts with the former understanding that random networks are preferable for spreading than regular networks. To describe the spreading in online social networks, a unknown-known-approved-exhausted four-status model was proposed, which emphasizes the effect of social reinforcement and assumes that the redundant signals can improve the probability of approval (i.e., the spreading rate). Performing the model on regular and random networks, it is found that our model can well explain the results of Centola's experiments on behavior spreading and some former studies on information spreading in different parameter space. The effects of average degree and network size on behavior spreading process are further analyzed. The results again show the importance of social reinforcement and are accordant with Centola's anticipation that increasing the network size or decreasing the average degree will enlarge the difference of the density of final approved nodes between regular and random networks. Our work complements the former studies on spreading dynamics, especially the spreading in online social networks where the information usually requires individuals' confirmations before being transmitted to others.

  18. Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.

    Science.gov (United States)

    Taamneh, Madhar; Taamneh, Salah; Alkheder, Sharaf

    2017-09-01

    Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too little attention has been paid to the differences between these accidents, leading, in most cases, to build less accurate predictors. Hierarchical clustering is a well-known clustering method that seeks to group data by creating a hierarchy of clusters. Using hierarchical clustering and ANNs, a clustering-based classification approach for predicting the injury severity of road traffic accidents was proposed. About 6000 road accidents occurred over a six-year period from 2008 to 2013 in Abu Dhabi were used throughout this study. In order to reduce the amount of variation in data, hierarchical clustering was applied on the data set to organize it into six different forms, each with different number of clusters (i.e., clusters from 1 to 6). Two ANN models were subsequently built for each cluster of accidents in each generated form. The first model was built and validated using all accidents (training set), whereas only 66% of the accidents were used to build the second model, and the remaining 34% were used to test it (percentage split). Finally, the weighted average accuracy was computed for each type of models in each from of data. The results show that when testing the models using the training set, clustering prior to classification achieves (11%-16%) more accuracy than without using clustering, while the percentage split achieves (2%-5%) more accuracy. The results also suggest that partitioning the accidents into six clusters achieves the best accuracy if both types of models are taken into account.

  19. Social Networking Sites and Language Learning

    Science.gov (United States)

    Brick, Billy

    2011-01-01

    This article examines a study of seven learners who logged their experiences on the language leaning social networking site Livemocha over a period of three months. The features of the site are described and the likelihood of their future success is considered. The learners were introduced to the Social Networking Site (SNS) and asked to learn a…

  20. Social Networking on the Semantic Web

    Science.gov (United States)

    Finin, Tim; Ding, Li; Zhou, Lina; Joshi, Anupam

    2005-01-01

    Purpose: Aims to investigate the way that the semantic web is being used to represent and process social network information. Design/methodology/approach: The Swoogle semantic web search engine was used to construct several large data sets of Resource Description Framework (RDF) documents with social network information that were encoded using the…

  1. Social Networking and Academic Performance: A Review

    Science.gov (United States)

    Doleck, Tenzin; Lajoie, Susanne

    2018-01-01

    The ubiquitous use of social networking sites by students and the potential impacts of such use on academic performance are of both theoretical and practical importance. Hence, this paper addresses the question: how does the use of social networking sites influence academic performance? The present review synthesizes the empirical findings of the…

  2. Collective Learning in Games through Social Networks

    NARCIS (Netherlands)

    Kosterman, S.; Gierasimczuk, N.; Armentano, M.G.; Monteserin, A.; Tang, J.; Yannibelli, V.

    2015-01-01

    This paper argues that combining social networks communication and games can positively influence the learning behavior of players. We propose a computational model that combines features of social network learning (communication) and game-based learning (strategy reinforcement). The focus is on

  3. The Social Dynamics of Innovation Networks

    NARCIS (Netherlands)

    Rutten, Roel; Benneworth, Paul Stephen; Irawati, Dessy; Boekema, Frans

    2014-01-01

    The social dynamics of innovation networks captures the important role of trust, social capital, institutions and norms and values in the creation of knowledge in innovation networks. In doing so, this book connects to a long-standing debate on the socio-spatial context of innovation in economic

  4. Social Networks and Corporate Information Security

    Directory of Open Access Journals (Sweden)

    Ekaterina Gennadievna Kondratova

    2013-06-01

    Full Text Available It is defined in the article social networks as a tool in the hands of cyber-criminals to compromise the organization’s data. The author focuses on a list of threats to information security caused by social networks usage, which should be considered in the set up of information security management system of the company.

  5. Social Networks: Gated Communities or Free Cantons?

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Online social networks and other cloud-based services have concentrated the control of the web in the hands of a few corporations. Our personal data has been commodified, often without our knowledge or consent. Is there a way to retain all the benefits of social networking without giving up control of our data?

  6. Designing for Privacy in Ubiquitous Social Networking

    DEFF Research Database (Denmark)

    Sapuppo, Antonio; Figueiras, Joao

    2015-01-01

    Improving human communication during face–to–face meetings is nowadays possible by transferring online social networking benefits to the physical world. This is enabled by the ubiquitous social networking services that became available by means of wirelessly interconnected smart devices...

  7. Entrepreneurial Idea Identification through Online Social Networks

    Science.gov (United States)

    Lang, Matthew C.

    2010-01-01

    The increasing use of social network websites may signal a change in the way the next generation of entrepreneurs identify entrepreneurial ideas. An important part of the entrepreneurship literature emphasizes how vital the use of social networks is to entrepreneurial idea identification, opportunity recognition, and ultimately new venture…

  8. Social networking for well-being

    NARCIS (Netherlands)

    Steen, M.G.D.; Aarts, O.A.J.; Broekman, C.C.M.T.; Prins, S.C.L.

    2011-01-01

    In this paper, we present some of the work that is being done in the WeCare project (in the AAL programme). The project’s goal is to introduce social networking services in the lives of older people, in order to improve their well-being. Participation in social networks, both online and ‘in real

  9. Social network sites: Indispensable or optional social tools?

    DEFF Research Database (Denmark)

    Shklovski, Irina

    2012-01-01

    Much research has enumerated potential benefits of online social network sites. Given the pervasiveness of these sites and the numbers of people that use them daily, both re-search and media tend to make the assumption that social network sites have become indispensible to their users. Based...... on the analysis of qualitative data from users of social network sites in Russia and Kazakhstan, this paper consid-ers under what conditions social network sites can become indispensable to their users and when these technologies remain on the periphery of life despite fulfilling useful func-tions. For some...... respondents, these sites had become indis-pensable tools as they were integrated into everyday rou-tines of communicating with emotionally important and proximal contacts and were often used for coordination of offline activities. For others social network sites remained spaces where they occasionally visited...

  10. Applications of social media and social network analysis

    CERN Document Server

    Kazienko, Przemyslaw

    2015-01-01

    This collection of contributed chapters demonstrates a wide range of applications within two overlapping research domains: social media analysis and social network analysis. Various methodologies were utilized in the twelve individual chapters including static, dynamic and real-time approaches to graph, textual and multimedia data analysis. The topics apply to reputation computation, emotion detection, topic evolution, rumor propagation, evaluation of textual opinions, friend ranking, analysis of public transportation networks, diffusion in dynamic networks, analysis of contributors to commun

  11. Predictive brain networks for major depression in a semi-multimodal fusion hierarchical feature reduction framework.

    Science.gov (United States)

    Yang, Jie; Yin, Yingying; Zhang, Zuping; Long, Jun; Dong, Jian; Zhang, Yuqun; Xu, Zhi; Li, Lei; Liu, Jie; Yuan, Yonggui

    2018-02-05

    Major depressive disorder (MDD) is characterized by dysregulation of distributed structural and functional networks. It is now recognized that structural and functional networks are related at multiple temporal scales. The recent emergence of multimodal fusion methods has made it possible to comprehensively and systematically investigate brain networks and thereby provide essential information for influencing disease diagnosis and prognosis. However, such investigations are hampered by the inconsistent dimensionality features between structural and functional networks. Thus, a semi-multimodal fusion hierarchical feature reduction framework is proposed. Feature reduction is a vital procedure in classification that can be used to eliminate irrelevant and redundant information and thereby improve the accuracy of disease diagnosis. Our proposed framework primarily consists of two steps. The first step considers the connection distances in both structural and functional networks between MDD and healthy control (HC) groups. By adding a constraint based on sparsity regularization, the second step fully utilizes the inter-relationship between the two modalities. However, in contrast to conventional multi-modality multi-task methods, the structural networks were considered to play only a subsidiary role in feature reduction and were not included in the following classification. The proposed method achieved a classification accuracy, specificity, sensitivity, and area under the curve of 84.91%, 88.6%, 81.29%, and 0.91, respectively. Moreover, the frontal-limbic system contributed the most to disease diagnosis. Importantly, by taking full advantage of the complementary information from multimodal neuroimaging data, the selected consensus connections may be highly reliable biomarkers of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Hierarchical graph-based segmentation for extracting road networks from high-resolution satellite images

    Science.gov (United States)

    Alshehhi, Rasha; Marpu, Prashanth Reddy

    2017-04-01

    Extraction of road networks in urban areas from remotely sensed imagery plays an important role in many urban applications (e.g. road navigation, geometric correction of urban remote sensing images, updating geographic information systems, etc.). It is normally difficult to accurately differentiate road from its background due to the complex geometry of the buildings and the acquisition geometry of the sensor. In this paper, we present a new method for extracting roads from high-resolution imagery based on hierarchical graph-based image segmentation. The proposed method consists of: 1. Extracting features (e.g., using Gabor and morphological filtering) to enhance the contrast between road and non-road pixels, 2. Graph-based segmentation consisting of (i) Constructing a graph representation of the image based on initial segmentation and (ii) Hierarchical merging and splitting of image segments based on color and shape features, and 3. Post-processing to remove irregularities in the extracted road segments. Experiments are conducted on three challenging datasets of high-resolution images to demonstrate the proposed method and compare with other similar approaches. The results demonstrate the validity and superior performance of the proposed method for road extraction in urban areas.

  13. Hierarchical Neural Representation of Dreamed Objects Revealed by Brain Decoding with Deep Neural Network Features.

    Science.gov (United States)

    Horikawa, Tomoyasu; Kamitani, Yukiyasu

    2017-01-01

    Dreaming is generally thought to be generated by spontaneous brain activity during sleep with patterns common to waking experience. This view is supported by a recent study demonstrating that dreamed objects can be predicted from brain activity during sleep using statistical decoders trained with stimulus-induced brain activity. However, it remains unclear whether and how visual image features associated with dreamed objects are represented in the brain. In this study, we used a deep neural network (DNN) model for object recognition as a proxy for hierarchical visual feature representation, and DNN features for dreamed objects were analyzed with brain decoding of fMRI data collected during dreaming. The decoders were first trained with stimulus-induced brain activity labeled with the feature values of the stimulus image from multiple DNN layers. The decoders were then used to decode DNN features from the dream fMRI data, and the decoded features were compared with the averaged features of each object category calculated from a large-scale image database. We found that the feature values decoded from the dream fMRI data positively correlated with those associated with dreamed object categories at mid- to high-level DNN layers. Using the decoded features, the dreamed object category could be identified at above-chance levels by matching them to the averaged features for candidate categories. The results suggest that dreaming recruits hierarchical visual feature representations associated with objects, which may support phenomenal aspects of dream experience.

  14. Diagnostics for generalized linear hierarchical models in network meta-analysis.

    Science.gov (United States)

    Zhao, Hong; Hodges, James S; Carlin, Bradley P

    2017-09-01

    Network meta-analysis (NMA) combines direct and indirect evidence comparing more than 2 treatments. Inconsistency arises when these 2 information sources differ. Previous work focuses on inconsistency detection, but little has been done on how to proceed after identifying inconsistency. The key issue is whether inconsistency changes an NMA's substantive conclusions. In this paper, we examine such discrepancies from a diagnostic point of view. Our methods seek to detect influential and outlying observations in NMA at a trial-by-arm level. These observations may have a large effect on the parameter estimates in NMA, or they may deviate markedly from other observations. We develop formal diagnostics for a Bayesian hierarchical model to check the effect of deleting any observation. Diagnostics are specified for generalized linear hierarchical NMA models and investigated for both published and simulated datasets. Results from our example dataset using either contrast- or arm-based models and from the simulated datasets indicate that the sources of inconsistency in NMA tend not to be influential, though results from the example dataset suggest that they are likely to be outliers. This mimics a familiar result from linear model theory, in which outliers with low leverage are not influential. Future extensions include incorporating baseline covariates and individual-level patient data. Copyright © 2017 John Wiley & Sons, Ltd.

  15. Hierarchical leak detection and localization method in natural gas pipeline monitoring sensor networks.

    Science.gov (United States)

    Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

    2012-01-01

    In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point's position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate.

  16. Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ning Yu

    2011-12-01

    Full Text Available In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate.

  17. Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

    Science.gov (United States)

    Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

    2012-01-01

    In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate. PMID:22368464

  18. Mining social networks and security informatics

    CERN Document Server

    Özyer, Tansel; Rokne, Jon; Khoury, Suheil

    2013-01-01

    Crime, terrorism and security are in the forefront of current societal concerns. This edited volume presents research based on social network techniques showing how data from crime and terror networks can be analyzed and how information can be extracted. The topics covered include crime data mining and visualization; organized crime detection; crime network visualization; computational criminology; aspects of terror network analyses and threat prediction including cyberterrorism and the related area of dark web; privacy issues in social networks; security informatics; graph algorithms for soci

  19. COMMUNICATION MANAGEMENT CRISIS IN SOCIAL NETWORKS

    OpenAIRE

    Ana Mª Enrique Jiménez

    2013-01-01

    It is often in the social networks where you detect the first signs of a potential crisis situation. Today, many companies decide to be present in social networks to communicate, listen and respond to their audiences openly with immediacy. A simple complaint is visible and propagates through the network in seconds, being capable of generating a negative impact on the corporate image of the organization. The same can happen to the contrary, ie, to praise the performance of a company, which may...

  20. Corporate Social Networking: Risks and Opportunities

    OpenAIRE

    Straumsheim, Jan Henrik Schou

    2011-01-01

    Social networks have seen an explosive growth over the last few years, with the most popular online services totaling over half a billion users. These networks have started permeating several aspects of our daily lives: for example by changing the ways we communicate with our friends and family, share media and organize events. Popular social networking websites like Facebook and Twitter now account for over half of the content shared on the web. Norwegian businesses are taking note, and are ...

  1. Hierarchically porous MgCo2O4 nanochain networks: template-free synthesis and catalytic application

    Science.gov (United States)

    Guan, Xiangfeng; Yu, Yunlong; Li, Xiaoyan; Chen, Dagui; Luo, Peihui; Zhang, Yu; Guo, Shanxin

    2018-01-01

    In this work, hierarchically porous MgCo2O4 nanochain networks were successfully synthesized by a novel template-free method realized via a facile solvothermal synthesis followed by a heat treatment. The morphologies of MgCo2O4 precursor could be adjusted from nanosheets to nanobelts and finally to interwoven nanowires, depending on the volume ratio of diethylene glycol to deionized water in the solution. After calcination, the interwoven precursor nanowires were transformed to hierarchical MgCo2O4 nanochain networks with marco-/meso-porosity, which are composed of 10-20 nm nanoparticles connected one by one. Moreover, the relative formation mechanism of the MgCo2O4 nanochain networks was discussed. More importantly, when evaluated as catalytic additive for AP thermal decomposition, the MgCo2O4 nanochain networks show excellent accelerating effect. It is benefited from the unique hierarchically porous network structure and multicomponent effect, which effectively accelerates ammonia oxidation and {{{{ClO}}}4}- species dissociation. This approach opens the way to design other hierarchically porous multicomponent metal oxides.

  2. Analyzing negative ties in social networks

    Directory of Open Access Journals (Sweden)

    Mankirat Kaur

    2016-03-01

    Full Text Available Online social networks are a source of sharing information and maintaining personal contacts with other people through social interactions and thus forming virtual communities online. Social networks are crowded with positive and negative relations. Positive relations are formed by support, endorsement and friendship and thus, create a network of well-connected users whereas negative relations are a result of opposition, distrust and avoidance creating disconnected networks. Due to increase in illegal activities such as masquerading, conspiring and creating fake profiles on online social networks, exploring and analyzing these negative activities becomes the need of hour. Usually negative ties are treated in same way as positive ties in many theories such as balance theory and blockmodeling analysis. But the standard concepts of social network analysis do not yield same results in respect of each tie. This paper presents a survey on analyzing negative ties in social networks through various types of network analysis techniques that are used for examining ties such as status, centrality and power measures. Due to the difference in characteristics of flow in positive and negative tie networks some of these measures are not applicable on negative ties. This paper also discusses new methods that have been developed specifically for analyzing negative ties such as negative degree, and h∗ measure along with the measures based on mixture of positive and negative ties. The different types of social network analysis approaches have been reviewed and compared to determine the best approach that can appropriately identify the negative ties in online networks. It has been analyzed that only few measures such as Degree and PN centrality are applicable for identifying outsiders in network. For applicability in online networks, the performance of PN measure needs to be verified and further, new measures should be developed based upon negative clique concept.

  3. Information filtering on coupled social networks.

    Science.gov (United States)

    Nie, Da-Cheng; Zhang, Zi-Ke; Zhou, Jun-Lin; Fu, Yan; Zhang, Kui

    2014-01-01

    In this paper, based on the coupled social networks (CSN), we propose a hybrid algorithm to nonlinearly integrate both social and behavior information of online users. Filtering algorithm, based on the coupled social networks, considers the effects of both social similarity and personalized preference. Experimental results based on two real datasets, Epinions and Friendfeed, show that the hybrid pattern can not only provide more accurate recommendations, but also enlarge the recommendation coverage while adopting global metric. Further empirical analyses demonstrate that the mutual reinforcement and rich-club phenomenon can also be found in coupled social networks where the identical individuals occupy the core position of the online system. This work may shed some light on the in-depth understanding of the structure and function of coupled social networks.

  4. Cardiovascular functioning, personality, and the social world: the domain of hierarchical power.

    Science.gov (United States)

    Newton, Tamara L

    2009-02-01

    The present paper considers connections between cardiovascular functioning (i.e., disease status and acute stress responses) and social dominance, and its counterpart, social submissiveness, both of which are part of the broader domain of "hierarchical power" [Bugental, D.B., 2000. Acquisition of the algorithms of social life: a domain-based approach. Psychological Bulletin 126, 187-219]. Empirical research on connections between dominance/submissiveness and cardiovascular morbidity and mortality in humans is reviewed, as is research on dominance/submissiveness and cardiovascular reactivity to, and recovery from, acute stressors. Three general conclusions are established. First, in both cross-sectional and longitudinal investigations, trait and behavioral indicators of dominance have been positively associated with cardiovascular disease severity, incidence, and progression, whereas preliminary evidence from two studies suggests that trait submissiveness may protect against poorer disease outcomes. Second, among men and women, trait dominance is associated with reactivity to and recovery from acute stressors, particularly social challenges. Third, linkages between dominance/submissiveness and cardiovascular functioning, especially cardiovascular reactivity, are characterized by gender-specific patterning, and this patterning emerges as a function of social context. Implications for the next generation of research concerning social dominance, gender, and cardiovascular functioning are discussed.

  5. Consumer engagement in social networks brand community

    OpenAIRE

    Rybakovas, Paulius

    2016-01-01

    Consumers increasingly integrate social media into their day-to-day lives. For companies consumer engagement in a brand community on social network is becoming increasingly important for developing relations with consumers. Consumer engagement in a brand community on social network creates a dynamic relationship between the community members and the brand which contributes to an increase in consumer loyalty to the brand. The literature is abundant of studies, which examines the consumer engag...

  6. Social Networks: Rational Learning and Information Aggregation

    Science.gov (United States)

    2009-09-01

    predecessor, Gale and Kariv (2003) who generalize the payoff equalization result of Bala and Goyal (1998) in connected social networks (discussed below...requires more notation. Using Bayes’ Rule and the assumption of equal priors on the state θ, we have that the social belief given by observing... Social Networks: Rational Learning and Information Aggregation by Ilan Lobel B.Sc., Pontif́ıcia Universidade Católica do Rio de Janeiro (2004

  7. Forest Monitoring and Wildland Early Fire Detection by a Hierarchical Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Antonio Molina-Pico

    2016-01-01

    Full Text Available A wildland fire is an uncontrolled fire that occurs mainly in forest areas, although it can also invade urban or agricultural areas. Among the main causes of wildfires, human factors, either intentional or accidental, are the most usual ones. The number and impact of forest fires are expected to grow as a consequence of the global warming. In order to fight against these disasters, it is necessary to adopt a comprehensive, multifaceted approach that enables a continuous situational awareness and instant responsiveness. This paper describes a hierarchical wireless sensor network aimed at early fire detection in risky areas, integrated with the fire fighting command centres, geographical information systems, and fire simulators. This configuration has been successfully tested in two fire simulations involving all the key players in fire fighting operations: fire brigades, communication systems, and aerial, coordination, and land means.

  8. Developmental evolution in social insects: regulatory networks from genes to societies.

    Science.gov (United States)

    Linksvayer, Timothy A; Fewell, Jennifer H; Gadau, Jürgen; Laubichler, Manfred D

    2012-05-01

    The evolution and development of complex phenotypes in social insect colonies, such as queen-worker dimorphism or division of labor, can, in our opinion, only be fully understood within an expanded mechanistic framework of Developmental Evolution. Conversely, social insects offer a fertile research area in which fundamental questions of Developmental Evolution can be addressed empirically. We review the concept of gene regulatory networks (GRNs) that aims to fully describe the battery of interacting genomic modules that are differentially expressed during the development of individual organisms. We discuss how distinct types of network models have been used to study different levels of biological organization in social insects, from GRNs to social networks. We propose that these hierarchical networks spanning different organizational levels from genes to societies should be integrated and incorporated into full GRN models to elucidate the evolutionary and developmental mechanisms underlying social insect phenotypes. Finally, we discuss prospects and approaches to achieve such an integration. © 2012 WILEY PERIODICALS, INC.

  9. Electropolymerized Star-Shaped Benzotrithiophenes Yield π-Conjugated Hierarchical Networks with High Areal Capacitance

    KAUST Repository

    Ringk, Andreas

    2016-03-30

    High-surface-area π-conjugated polymeric networks have the potential to lend outstanding capacitance to supercapacitors because of the pronounced faradaic processes that take place across the dense intimate interface between active material and electrolytes. In this report, we describe how benzo[1,2-b:3,4-b’:5,6-b’’]trithiophene (BTT) and tris-EDOT-benzo[1,2-b:3,4-b’:5,6-b’’]trithiophene (TEBTT) can serve as 2D (trivalent) building blocks in the development of electropolymerized hierarchical π-conjugated frameworks with particularly high areal capacitance. In comparing electropolymerized networks of BTT, TEBTT, and their copolymers with EDOT, we show that P(TEBTT/EDOT)-based frameworks can achieve higher areal capacitance (e.g., as high as 443.8 mF cm-2 at 1 mA cm-2) than those achieved by their respective homopolymers (PTEBTT and PEDOT) in the same experimental conditions of electrodeposition (PTEBTT: 271.1 mF cm-2 (at 1 mA cm-2) and PEDOT: 12.1 mF cm-2 (at 1 mA cm-2)). For example, P(TEBTT/EDOT)-based frameworks synthesized in a 1:1 monomer-to-comonomer ratio show a ca. 35x capacitance improvement over PEDOT. The high areal capacitance measured for P(TEBTT/EDOT) copolymers can be explained by the open, highly porous hierarchical morphologies formed during the electropolymerization step. With >70% capacitance retention over 1,000 cycles (up to 89% achieved), both PTEBTT- and P(TEBTT/EDOT)-based frameworks are resilient to repeated electrochemical cycling and can be considered promising systems for high life cycle capacitive electrode applications.

  10. Electropolymerized Star-Shaped Benzotrithiophenes Yield π-Conjugated Hierarchical Networks with High Areal Capacitance

    KAUST Repository

    Ringk, Andreas; Lignie, Adrien; Hou, Yuanfang; Alshareef, Husam N.; Beaujuge, Pierre

    2016-01-01

    High-surface-area π-conjugated polymeric networks have the potential to lend outstanding capacitance to supercapacitors because of the pronounced faradaic processes that take place across the dense intimate interface between active material and electrolytes. In this report, we describe how benzo[1,2-b:3,4-b’:5,6-b’’]trithiophene (BTT) and tris-EDOT-benzo[1,2-b:3,4-b’:5,6-b’’]trithiophene (TEBTT) can serve as 2D (trivalent) building blocks in the development of electropolymerized hierarchical π-conjugated frameworks with particularly high areal capacitance. In comparing electropolymerized networks of BTT, TEBTT, and their copolymers with EDOT, we show that P(TEBTT/EDOT)-based frameworks can achieve higher areal capacitance (e.g., as high as 443.8 mF cm-2 at 1 mA cm-2) than those achieved by their respective homopolymers (PTEBTT and PEDOT) in the same experimental conditions of electrodeposition (PTEBTT: 271.1 mF cm-2 (at 1 mA cm-2) and PEDOT: 12.1 mF cm-2 (at 1 mA cm-2)). For example, P(TEBTT/EDOT)-based frameworks synthesized in a 1:1 monomer-to-comonomer ratio show a ca. 35x capacitance improvement over PEDOT. The high areal capacitance measured for P(TEBTT/EDOT) copolymers can be explained by the open, highly porous hierarchical morphologies formed during the electropolymerization step. With >70% capacitance retention over 1,000 cycles (up to 89% achieved), both PTEBTT- and P(TEBTT/EDOT)-based frameworks are resilient to repeated electrochemical cycling and can be considered promising systems for high life cycle capacitive electrode applications.

  11. Hierarchical surface code for network quantum computing with modules of arbitrary size

    Science.gov (United States)

    Li, Ying; Benjamin, Simon C.

    2016-10-01

    The network paradigm for quantum computing involves interconnecting many modules to form a scalable machine. Typically it is assumed that the links between modules are prone to noise while operations within modules have a significantly higher fidelity. To optimize fault tolerance in such architectures we introduce a hierarchical generalization of the surface code: a small "patch" of the code exists within each module and constitutes a single effective qubit of the logic-level surface code. Errors primarily occur in a two-dimensional subspace, i.e., patch perimeters extruded over time, and the resulting noise threshold for intermodule links can exceed ˜10 % even in the absence of purification. Increasing the number of qubits within each module decreases the number of qubits necessary for encoding a logical qubit. But this advantage is relatively modest, and broadly speaking, a "fine-grained" network of small modules containing only about eight qubits is competitive in total qubit count versus a "course" network with modules containing many hundreds of qubits.

  12. A Persistent Structured Hierarchical Overlay Network to Counter Intentional Churn Attack

    Directory of Open Access Journals (Sweden)

    Ramanpreet Kaur

    2016-01-01

    Full Text Available The increased use of structured overlay network for a variety of applications has attracted a lot of attention from both research community and attackers. However, the structural constraints, open nature (anybody can join and anybody may leave, and unreliability of its participant nodes significantly affect the performance of these applications and make it vulnerable to a variety of attacks such as eclipse, Sybil, and churn. One attack to compromise the service availability in overlay network is intentional churn (join/leave attack, where a large number of malicious users will join and leave the overlay network so frequently that the entire structure collapses and becomes unavailable. The focus of this paper is to provide a new robust, efficient, and scalable hierarchical overlay architecture that will counter these attacks by providing a structure that can accommodate the fleeting behaviour of nodes without causing much structural inconsistencies. The performance evaluation showed that the proposed architecture has more failure resilience and self-organization as compared to chord based architecture. Experimental results have demonstrated that the effect of failures on an overlay is proportional to the size of failure.

  13. Social Network Sites, Individual Social Capital and Happiness

    NARCIS (Netherlands)

    E. Arampatzi (Efstratia); M.J. Burger (Martijn); N.A. Novik (Natallia)

    2016-01-01

    textabstractCan online social contacts replace the importance of real-life social connections in our pursuit of happiness? With the growing use of social network sites (SNSs), attention has been increasingly drawn to this topic. Our study empirically examines the effect of SNS use on happiness for

  14. One Health in social networks and social media.

    Science.gov (United States)

    Mekaru, S R; Brownstein, J S

    2014-08-01

    In the rapidly evolving world of social media, social networks, mobile applications and citizen science, online communities can develop organically and separately from larger or more established organisations. The One Health online community is experiencing expansion from both the bottom up and the top down. In this paper, the authors review social media's strengths and weaknesses, earlier work examining Internet resources for One Health, the current state of One Health in social media (e.g. Facebook, Twitter, YouTube) and online social networking sites (e.g. LinkedIn and ResearchGate), as well as social media in One Health-related citizen science projects. While One Health has a fairly strong presence on websites, its social media presence is more limited and has an uneven geographic distribution. In work following the Stone Mountain Meeting,the One Health Global Network Task Force Report recommended the creation of an online community of practice. Professional social networks as well as the strategic use of social media should be employed in this effort. Finally, One Health-related research projects using volunteers (citizen science) often use social media to enhance their recruitment. Including these researchers in a community of practitioners would take full advantage of their existing social media presence. In conclusion, the interactive nature of social media, combined with increasing global Internet access, provides the One Health community with opportunities to meaningfully expand their community and promote their message.

  15. Spreading paths in partially observed social networks

    OpenAIRE

    Onnela, Jukka-Pekka; Christakis, Nicholas A.

    2012-01-01

    Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using a static, s...

  16. Modeling online social signed networks

    Science.gov (United States)

    Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru

    2018-04-01

    People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.

  17. Web Mining and Social Networking

    DEFF Research Database (Denmark)

    Xu, Guandong; Zhang, Yanchun; Li, Lin

    This book examines the techniques and applications involved in the Web Mining, Web Personalization and Recommendation and Web Community Analysis domains, including a detailed presentation of the principles, developed algorithms, and systems of the research in these areas. The applications of web ...... sense of individuals or communities. The volume will benefit both academic and industry communities interested in the techniques and applications of web search, web data management, web mining and web knowledge discovery, as well as web community and social network analysis.......This book examines the techniques and applications involved in the Web Mining, Web Personalization and Recommendation and Web Community Analysis domains, including a detailed presentation of the principles, developed algorithms, and systems of the research in these areas. The applications of web...... mining, and the issue of how to incorporate web mining into web personalization and recommendation systems are also reviewed. Additionally, the volume explores web community mining and analysis to find the structural, organizational and temporal developments of web communities and reveal the societal...

  18. Organ trade using social networks.

    Science.gov (United States)

    Alrogy, Waleed; Jawdat, Dunia; Alsemari, Muhannad; Alharbi, Abdulrahman; Alasaad, Abdullah; Hajeer, Ali H

    2016-01-01

    Organ transplantation is recognized worldwide as an effective treatment for organ failure. However, due to the increase in the number of patients requiring a transplant, a shortage of suitable organs for transplantation has become a global problem. Human organ trade is an illegal practice of buying or selling organs and is universally sentenced. The aim of this study was to search social network for organ trade and offerings in Saudi Arabia. The study was conducted from June 22, 2015 to February 19, 2016. The search was conducted on Twitter, Google answers, and Facebook using the following terms: kidney for sale, kidneys for sale, liver for sale, kidney wanted, liver wanted, kidney donor, and liver donor. We found a total of 557 adverts on organ trade, 165 (30%) from donors or sellers, and 392 (70%) from recipients or buyers. On Twitter, we found 472 (85%) adverts, on Google answers 61 (11%), and on Facebook 24 (4%). Organ trade is a global problem, and yet it is increasingly seen in many countries. Although the Saudi Center for Organ Transplantation by-laws specifically prohibits and monitors any form of commercial transplantation, it is still essential to enforce guidelines for medical professionals to detect and prevent such criminal acts.

  19. Organ trade using social networks

    Directory of Open Access Journals (Sweden)

    Waleed Alrogy

    2016-01-01

    Full Text Available Organ transplantation is recognized worldwide as an effective treatment for organ failure. However, due to the increase in the number of patients requiring a transplant, a shortage of suitable organs for transplantation has become a global problem. Human organ trade is an illegal practice of buying or selling organs and is universally sentenced. The aim of this study was to search social network for organ trade and offerings in Saudi Arabia. The study was conducted from June 22, 2015 to February 19, 2016. The search was conducted on Twitter, Google answers, and Facebook using the following terms: kidney for sale, kidneys for sale, liver for sale, kidney wanted, liver wanted, kidney donor, and liver donor. We found a total of 557 adverts on organ trade, 165 (30% from donors or sellers, and 392 (70% from recipients or buyers. On Twitter, we found 472 (85% adverts, on Google answers 61 (11%, and on Facebook 24 (4%. Organ trade is a global problem, and yet it is increasingly seen in many countries. Although the Saudi Center for Organ Transplantation by-laws specifically prohibits and monitors any form of commercial transplantation, it is still essential to enforce guidelines for medical professionals to detect and prevent such criminal acts.

  20. Brand communities embedded in social networks ?

    OpenAIRE

    Zaglia, Melanie E.

    2013-01-01

    Brand communities represent highly valuable marketing, innovation management, and customer relationship management tools. However, applying successful marketing strategies today, and in the future, also means exploring and seizing the unprecedented opportunities of social network environments. This study combines these two social phenomena which have largely been researched separately, and aims to investigate the existence, functionality and different types of brand communities within social ...

  1. Modern Social Support Structures: Online Social Networks and their Implications for Social Workers

    Directory of Open Access Journals (Sweden)

    Kala Chakradhar

    2009-03-01

    Full Text Available Mapping and assessing social networks and the quality of their social support is a valuable intervention strategy for social workers. These networks have now spread onto the digital realm in the form of Online Social Networks (OSNs. This study investigated the nature of social support provided by such networks to their users in a rural mid-South University (USA and explored parallels with the current understanding of social support in conventional social networks. A web-based survey administered to college students revealed that users of these online networks were predominantly undergraduate first year students, female, single, unemployed and from a variety of academic disciplines. The examination of the components of OSNs appears to mirror those of offline networks. They also seem to complement the effects of each other while contributing to an individual's support system. The paper concludes with critical implications of such online social networking for University students and social workers in practice and education.

  2. The Social Origins of Networks and Diffusion.

    Science.gov (United States)

    Centola, Damon

    2015-03-01

    Recent research on social contagion has demonstrated significant effects of network topology on the dynamics of diffusion. However, network topologies are not given a priori. Rather, they are patterns of relations that emerge from individual and structural features of society, such as population composition, group heterogeneity, homophily, and social consolidation. Following Blau and Schwartz, the author develops a model of social network formation that explores how social and structural constraints on tie formation generate emergent social topologies and then explores the effectiveness of these social networks for the dynamics of social diffusion. Results show that, at one extreme, high levels of consolidation can create highly balkanized communities with poor integration of shared norms and practices. As suggested by Blau and Schwartz, reducing consolidation creates more crosscutting circles and significantly improves the dynamics of social diffusion across the population. However, the author finds that further reducing consolidation creates highly intersecting social networks that fail to support the widespread diffusion of norms and practices, indicating that successful social diffusion can depend on moderate to high levels of structural consolidation.

  3. [Social networks in drinking behaviors among Japanese: support network, drinking network, and intervening network].

    Science.gov (United States)

    Yoshihara, Chika; Shimizu, Shinji

    2005-10-01

    The national representative sample was analyzed to examine the relationship between respondents' drinking practice and the social network which was constructed of three different types of network: support network, drinking network, and intervening network. Non-parametric statistical analysis was conducted with chi square method and ANOVA analysis, due to the risk of small samples in some basic tabulation cells. The main results are as follows: (1) In the support network of workplace associates, moderate drinkers enjoyed much more sociable support care than both nondrinkers and hard drinkers, which might suggest a similar effect as the French paradox. Meanwhile in the familial and kinship network, the more intervening care support was provided, the harder respondents' drinking practice. (2) The drinking network among Japanese people for both sexes is likely to be convergent upon certain types of network categories and not decentralized in various categories. This might reflect of the drinking culture of Japan, which permits people to drink everyday as a practice, especially male drinkers. Subsequently, solitary drinking is not optional for female drinkers. (3) Intervening network analysis showed that the harder the respondents' drinking practices, the more frequently their drinking behaviors were checked in almost all the categories of network. A rather complicated gender double-standard was found in the network of hard drinkers with their friends, particularly for female drinkers. Medical professionals played a similar intervening role for men as family and kinship networks but to a less degree than friends for females. The social network is considerably associated with respondents' drinking, providing both sociability for moderate drinkers and intervention for hard drinkers, depending on network categories. To minimize the risk of hard drinking and advance self-healthy drinking there should be more research development on drinking practice and the social network.

  4. SOCIAL NETWORKS AS DISPOSITIVES OF NEOLIBERAL GOVERNMENTALITY

    Directory of Open Access Journals (Sweden)

    Julio Cesar Lemes de Castro

    2016-10-01

    Full Text Available This article of theoretical reflection investigates the social networks that emerge in the context of Web 2.0, such as Facebook, as dispositives of neoliberal governmentality in the sense proposed by Foucault. From the standpoint of government of self, the design of social networks establishes a competition for attention that tends to favor the neoliberal culture of performance. In terms of social organization, the way in which users intertwine their connections is paralleled by the neoliberal paradigm of spontaneous market order. Furthermore, the use of personal information on these users, encompassing all their activities within the networks, in order to set up databases to attract advertisers reflects the neoliberal tendency of colonization of the different realms of existence by economic forces. However, the tensions that accompany neoliberal governmentality in social networks reveal its limitations, opening the possibility for these networks to also act as instruments of resistance to neoliberalism.

  5. Social networks a framework of computational intelligence

    CERN Document Server

    Chen, Shyi-Ming

    2014-01-01

    This volume provides the audience with an updated, in-depth and highly coherent material on the conceptually appealing and practically sound information technology of Computational Intelligence applied to the analysis, synthesis and evaluation of social networks. The volume involves studies devoted to key issues of social networks including community structure detection in networks, online social networks, knowledge growth and evaluation, and diversity of collaboration mechanisms.  The book engages a wealth of methods of Computational Intelligence along with well-known techniques of linear programming, Formal Concept Analysis, machine learning, and agent modeling.  Human-centricity is of paramount relevance and this facet manifests in many ways including personalized semantics, trust metric, and personal knowledge management; just to highlight a few of these aspects. The contributors to this volume report on various essential applications including cyber attacks detection, building enterprise social network...

  6. Contributions of Social Networking for Innovation

    Directory of Open Access Journals (Sweden)

    Daniela Maria Cartoni

    2013-04-01

    Full Text Available This paper investigates the role of virtual social networks as a mechanism complementary to formal channels of technology transfer represented by ICT and by private centers of R & D in industry. The strengthening of Web 2.0 has provided the expansion of collaborative tools, in particular the social networks, with a strong influence on the spread of knowledge and innovation. To evaluate the potential of virtual networks, a survey had been conducted to identify and describe the characteristics of some of the major social networks used in Brazil (LinkedIn, Orkut and Twitter. Even this phenomenon is not mature, the study identified the potential and benefits of social networks as informal structures that help in generation of knowledge and innovation diffusion, as a field to be explored and developed.

  7. The use of hierarchical clustering for the design of optimized monitoring networks

    Science.gov (United States)

    Soares, Joana; Makar, Paul Andrew; Aklilu, Yayne; Akingunola, Ayodeji

    2018-05-01

    Associativity analysis is a powerful tool to deal with large-scale datasets by clustering the data on the basis of (dis)similarity and can be used to assess the efficacy and design of air quality monitoring networks. We describe here our use of Kolmogorov-Zurbenko filtering and hierarchical clustering of NO2 and SO2 passive and continuous monitoring data to analyse and optimize air quality networks for these species in the province of Alberta, Canada. The methodology applied in this study assesses dissimilarity between monitoring station time series based on two metrics: 1 - R, R being the Pearson correlation coefficient, and the Euclidean distance; we find that both should be used in evaluating monitoring site similarity. We have combined the analytic power of hierarchical clustering with the spatial information provided by deterministic air quality model results, using the gridded time series of model output as potential station locations, as a proxy for assessing monitoring network design and for network optimization. We demonstrate that clustering results depend on the air contaminant analysed, reflecting the difference in the respective emission sources of SO2 and NO2 in the region under study. Our work shows that much of the signal identifying the sources of NO2 and SO2 emissions resides in shorter timescales (hourly to daily) due to short-term variation of concentrations and that longer-term averages in data collection may lose the information needed to identify local sources. However, the methodology identifies stations mainly influenced by seasonality, if larger timescales (weekly to monthly) are considered. We have performed the first dissimilarity analysis based on gridded air quality model output and have shown that the methodology is capable of generating maps of subregions within which a single station will represent the entire subregion, to a given level of dissimilarity. We have also shown that our approach is capable of identifying different

  8. Social network analysis of study environment

    Directory of Open Access Journals (Sweden)

    Blaženka Divjak

    2010-06-01

    Full Text Available Student working environment influences student learning and achievement level. In this respect social aspects of students’ formal and non-formal learning play special role in learning environment. The main research problem of this paper is to find out if students' academic performance influences their position in different students' social networks. Further, there is a need to identify other predictors of this position. In the process of problem solving we use the Social Network Analysis (SNA that is based on the data we collected from the students at the Faculty of Organization and Informatics, University of Zagreb. There are two data samples: in the basic sample N=27 and in the extended sample N=52. We collected data on social-demographic position, academic performance, learning and motivation styles, student status (full-time/part-time, attitudes towards individual and teamwork as well as informal cooperation. Afterwards five different networks (exchange of learning materials, teamwork, informal communication, basic and aggregated social network were constructed. These networks were analyzed with different metrics and the most important were betweenness, closeness and degree centrality. The main result is, firstly, that the position in a social network cannot be forecast only by academic success and, secondly, that part-time students tend to form separate groups that are poorly connected with full-time students. In general, position of a student in social networks in study environment can influence student learning as well as her/his future employability and therefore it is worthwhile to be investigated.

  9. Volunteerism: Social Network Dynamics and Education

    Science.gov (United States)

    Ajrouch, Kristine J.; Antonucci, Toni C.; Webster, Noah J.

    2016-01-01

    Objectives . We examine how changes in social networks influence volunteerism through bridging (diversity) and bonding (spending time) mechanisms. We further investigate whether social network change substitutes or amplifies the effects of education on volunteerism. Methods . Data (n = 543) are drawn from a two-wave survey of Social Relations and Health over the Life Course (SRHLC). Zero-inflated negative binomial regressions were conducted to test competing hypotheses about how changes in social network characteristics alone and in conjunction with education level predict likelihood and frequency of volunteering. Results . Changes in social networks were associated with volunteerism: as the proportion of family members decreased and the average number of network members living within a one-hour drive increased over time, participants reported higher odds of volunteering. The substitution hypothesis was supported: social networks that exhibited more geographic proximity and greater contact frequency over-time compensated for lower levels of education to predict volunteering more hours. Discussion . The dynamic role of social networks and the ways in which they may work through bridging and bonding to influence both likelihood and frequency of volunteering are discussed. The potential benefits of volunteerism in light of longer life expectancies and smaller families are also considered. PMID:25512570

  10. Synchronization of Hierarchical Time-Varying Neural Networks Based on Asynchronous and Intermittent Sampled-Data Control.

    Science.gov (United States)

    Xiong, Wenjun; Patel, Ragini; Cao, Jinde; Zheng, Wei Xing

    In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.

  11. COalitions in COOperation Networks (COCOON): Social Network Analysis and Game Theory to Enhance Cooperation Networks

    NARCIS (Netherlands)

    Sie, Rory

    2012-01-01

    Sie, R. L. L. (2012). COalitions in COOperation Networks (COCOON): Social Network Analysis and Game Theory to Enhance Cooperation Networks (Unpublished doctoral dissertation). September, 28, 2012, Open Universiteit in the Netherlands (CELSTEC), Heerlen, The Netherlands.

  12. Urbanism, Neighborhood Context, and Social Networks.

    Science.gov (United States)

    Cornwell, Erin York; Behler, Rachel L

    2015-09-01

    Theories of urbanism suggest that the urban context erodes individuals' strong social ties with friends and family. Recent research has narrowed focus to the neighborhood context, emphasizing how localized structural disadvantage affects community-level cohesion and social capital. In this paper, we argue that neighborhood context also shapes social ties with friends and family- particularly for community-dwelling seniors. We hypothesize that neighborhood disadvantage, residential instability, and disorder restrict residents' abilities to cultivate close relationships with neighbors and non-neighbor friends and family. Using data from the National Social Life, Health, and Aging Project (NSHAP), we find that older adults who live in disadvantaged neighborhoods have smaller social networks. Neighborhood disadvantage is also associated with less close network ties and less frequent interaction - but only among men. Furthermore, residents of disordered neighborhoods have smaller networks and weaker ties. We urge scholars to pay greater attention to how neighborhood context contributes to disparities in network-based access to resources.

  13. Benford's Law Applies to Online Social Networks.

    Science.gov (United States)

    Golbeck, Jennifer

    2015-01-01

    Benford's Law states that, in naturally occurring systems, the frequency of numbers' first digits is not evenly distributed. Numbers beginning with a 1 occur roughly 30% of the time, and are six times more common than numbers beginning with a 9. We show that Benford's Law applies to social and behavioral features of users in online social networks. Using social data from five major social networks (Facebook, Twitter, Google Plus, Pinterest, and LiveJournal), we show that the distribution of first significant digits of friend and follower counts for users in these systems follow Benford's Law. The same is true for the number of posts users make. We extend this to egocentric networks, showing that friend counts among the people in an individual's social network also follows the expected distribution. We discuss how this can be used to detect suspicious or fraudulent activity online and to validate datasets.

  14. Benford's Law Applies to Online Social Networks.

    Directory of Open Access Journals (Sweden)

    Jennifer Golbeck

    Full Text Available Benford's Law states that, in naturally occurring systems, the frequency of numbers' first digits is not evenly distributed. Numbers beginning with a 1 occur roughly 30% of the time, and are six times more common than numbers beginning with a 9. We show that Benford's Law applies to social and behavioral features of users in online social networks. Using social data from five major social networks (Facebook, Twitter, Google Plus, Pinterest, and LiveJournal, we show that the distribution of first significant digits of friend and follower counts for users in these systems follow Benford's Law. The same is true for the number of posts users make. We extend this to egocentric networks, showing that friend counts among the people in an individual's social network also follows the expected distribution. We discuss how this can be used to detect suspicious or fraudulent activity online and to validate datasets.

  15. Method of Parallel-Hierarchical Network Self-Training and its Application for Pattern Classification and Recognition

    Directory of Open Access Journals (Sweden)

    TIMCHENKO, L.

    2012-11-01

    Full Text Available Propositions necessary for development of parallel-hierarchical (PH network training methods are discussed in this article. Unlike already known structures of the artificial neural network, where non-normalized (absolute similarity criteria are used for comparison, the suggested structure uses a normalized criterion. Based on the analysis of training rules, a conclusion is made that application of two training methods with a teacher is optimal for PH network training: error correction-based training and memory-based training. Mathematical models of training and a combined method of PH network training for recognition of static and dynamic patterns are developed.

  16. Regional Use of Social Networking Tools

    Science.gov (United States)

    2014-12-01

    4 2.1.7 Tumblr 4 2.1.8 Instagram 4 2.2 Local Social Networking Services 5 3 Regional Preferences for Social Networking Tools 6 4 African Region...YouTube 280 million Twitter 255 million LinkedIn n/a Pinterest n/a Tumblr 300 million Instagram 200 million The active-user base numbers...so this percentage may decline in the future. 2.1.8 Instagram Instagram , acquired by Facebook in 2012, is a mobile social networking service that

  17. The genre tutorial and social networks terminology

    Directory of Open Access Journals (Sweden)

    Márcio Sales Santiago

    2014-02-01

    Full Text Available This paper analyzes the terminology in the Internet social networks tutorials. A tutorial is a specialized text, full of terms, aiming to teach an individual or group of individuals who need some guidelines to operationalize a computerized tool, such as a social network. It is necessary to identify linguistic and terminological characteristics from the specialized lexical units in this digital genre. Social networks terminology is described and exemplified here. The results show that it is possible to refer to two specific terminologies in tutorials which help to determine the terminological profile of the thematic area, specifically from the point of view of denomination.

  18. Evolution of individual versus social learning on social networks.

    Science.gov (United States)

    Tamura, Kohei; Kobayashi, Yutaka; Ihara, Yasuo

    2015-03-06

    A number of studies have investigated the roles played by individual and social learning in cultural phenomena and the relative advantages of the two learning strategies in variable environments. Because social learning involves the acquisition of behaviours from others, its utility depends on the availability of 'cultural models' exhibiting adaptive behaviours. This indicates that social networks play an essential role in the evolution of learning. However, possible effects of social structure on the evolution of learning have not been fully explored. Here, we develop a mathematical model to explore the evolutionary dynamics of learning strategies on social networks. We first derive the condition under which social learners (SLs) are selectively favoured over individual learners in a broad range of social network. We then obtain an analytical approximation of the long-term average frequency of SLs in homogeneous networks, from which we specify the condition, in terms of three relatedness measures, for social structure to facilitate the long-term evolution of social learning. Finally, we evaluate our approximation by Monte Carlo simulations in complete graphs, regular random graphs and scale-free networks. We formally show that whether social structure favours the evolution of social learning is determined by the relative magnitudes of two effects of social structure: localization in competition, by which competition between learning strategies is evaded, and localization in cultural transmission, which slows down the spread of adaptive traits. In addition, our estimates of the relatedness measures suggest that social structure disfavours the evolution of social learning when selection is weak. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  19. The dynamics of social networks among female Asian elephants

    Directory of Open Access Journals (Sweden)

    de Silva Shermin

    2011-07-01

    Full Text Available Abstract Background Patterns in the association of individuals can shed light on the underlying conditions and processes that shape societies. Here we characterize patterns of association in a population of wild Asian Elephants at Uda Walawe National Park in Sri Lanka. We observed 286 individually-identified adult female elephants over 20 months and examined their social dynamics at three levels of organization: pairs of individuals (dyads, small sets of direct companions (ego-networks, and the population level (complete networks. Results Corroborating previous studies of this and other Asian elephant populations, we find that the sizes of elephant groups observed in the field on any particular day are typically small and that rates of association are low. In contrast to earlier studies, our longitudinal observations reveal that individuals form larger social units that can be remarkably stable across years while associations among such units change across seasons. Association rates tend to peak in dry seasons as opposed to wet seasons, with some cyclicity at the level of dyads. In addition, we find that individuals vary substantially in their fidelity to companions. At the ego-network level, we find that despite these fluctuations, individuals associate with a pool of long-term companions. At the population level, social networks do not exhibit any clear seasonal structure or hierarchical stratification. Conclusions This detailed longitudinal study reveals different social dynamics at different levels of organization. Taken together, these results demonstrate that low association rates, seemingly small group sizes, and fission-fusion grouping behavior mask hidden stability in the extensive and fluid social affiliations in this population of Asian elephants.

  20. Social Networks and Social Revolution. Evidence from Romania

    Directory of Open Access Journals (Sweden)

    Androniciuc Andra

    2017-01-01

    No other means of communication have had such a rapid development as the Internet, a mediumthat is undoubtedly changing the rules of the political game. In this article, we take a look at theuse of social networks during social and political movements, with particular focus on the 2014,2015 and 2017 Romanian protests. We conclude that social networks alone do not instigaterevolutions, but they are valuable tools for citizens to organize free protests, recruit and trainparticipants, which can lead to further collective action and social change.

  1. Maintenance of cultural diversity: social roles, social networks, and cognitive networks.

    Science.gov (United States)

    Abrams, Marshall

    2014-06-01

    Smaldino suggests that patterns that give rise to group-level cultural traits can also increase individual-level cultural diversity. I distinguish social roles and related social network structures and discuss ways in which each might maintain diversity. I suggest that cognitive analogs of "cohesion," a property of networks that helps maintenance of diversity, might mediate the effects of social roles on diversity.

  2. Hierarchical structure and modules in the Escherichia coli transcriptional regulatory network revealed by a new top-down approach

    Directory of Open Access Journals (Sweden)

    Buer Jan

    2004-12-01

    Full Text Available Abstract Background Cellular functions are coordinately carried out by groups of genes forming functional modules. Identifying such modules in the transcriptional regulatory network (TRN of organisms is important for understanding the structure and function of these fundamental cellular networks and essential for the emerging modular biology. So far, the global connectivity structure of TRN has not been well studied and consequently not applied for the identification of functional modules. Moreover, network motifs such as feed forward loop are recently proposed to be basic building blocks of TRN. However, their relationship to functional modules is not clear. Results In this work we proposed a top-down approach to identify modules in the TRN of E. coli. By studying the global connectivity structure of the regulatory network, we first revealed a five-layer hierarchical structure in which all the regulatory relationships are downward. Based on this regulatory hierarchy, we developed a new method to decompose the regulatory network into functional modules and to identify global regulators governing multiple modules. As a result, 10 global regulators and 39 modules were identified and shown to have well defined functions. We then investigated the distribution and composition of the two basic network motifs (feed forward loop and bi-fan motif in the hierarchical structure of TRN. We found that most of these network motifs include global regulators, indicating that these motifs are not basic building blocks of modules since modules should not contain global regulators. Conclusion The transcriptional regulatory network of E. coli possesses a multi-layer hierarchical modular structure without feedback regulation at transcription level. This hierarchical structure builds the basis for a new and simple decomposition method which is suitable for the identification of functional modules and global regulators in the transcriptional regulatory network of E

  3. Social networking policies in nursing education.

    Science.gov (United States)

    Frazier, Blake; Culley, Joan M; Hein, Laura C; Williams, Amber; Tavakoli, Abbas S

    2014-03-01

    Social networking use has increased exponentially in the past few years. A literature review related to social networking and nursing revealed a research gap between nursing practice and education. Although there was information available on the appropriate use of social networking sites, there was limited research on the use of social networking policies within nursing education. The purpose of this study was to identify current use of social media by faculty and students and a need for policies within nursing education at one institution. A survey was developed and administered to nursing students (n = 273) and nursing faculty (n = 33). Inferential statistics included χ², Fisher exact test, t test, and General Linear Model. Cronbach's α was used to assess internal consistency of social media scales. The χ² result indicates that there were associations with the group and several social media items. t Test results indicate significant differences between student and faculty for average of policies are good (P = .0127), policies and discipline (P = .0315), and policy at the study school (P = .0013). General Linear Model analyses revealed significant differences for "friend" a patient with a bond, unprofessional posts, policy, and nursing with class level. Results showed that students and faculty supported the development of a social networking policy.

  4. Hierarchical ZnO microspheres built by sheet-like network: Large-scale synthesis and structurally enhanced catalytic performances

    International Nuclear Information System (INIS)

    Zhu Guoxing; Liu Yuanjun; Ji Zhenyuan; Bai Song; Shen Xiaoping; Xu Zheng

    2012-01-01

    Highlights: ► Hierarchical ZnO microspheres were prepared through a facile precursor procedure in the absence of self-assembled templates, organic additives, or matrices. ► The building blocks of microspheres, sheet-like ZnO networks, are porous mesocrystal terminated with (0 1 −1 0) crystal planes. ► The hierarchical ZnO microsphere catalyst exhibits structure-induced enhancement of catalytic performance and a strong durability. - Abstract: Large-scale novel hierarchical ZnO microspheres were fabricated by a facile precursor procedure in the absence of self-assembled templates, organic additives, or matrices. A field emission scanning electron microscopy (FESEM) image reveals that the ZnO microspheres with diameter of 5–18 μm are built by sheet-like ZnO networks with average thickness of 40 nm and length of several microns. High resolution transmission electron microscopy (HRTEM) image indicates that the building blocks, sheet-like ZnO networks, are porous mesocrystal terminated with {0 1 −1 0} crystal planes. A potential application of the ZnO microspheres as a catalyst in the synthesis of 5-substituted 1H-tetrazoles was investigated. It was found that the hierarchical ZnO microsphere catalyst exhibits structure-induced enhancement of catalytic performance and a strong durability.

  5. A Multidimensional and Multimembership Clustering Method for Social Networks and Its Application in Customer Relationship Management

    Directory of Open Access Journals (Sweden)

    Peixin Zhao

    2013-01-01

    Full Text Available Community detection in social networks plays an important role in cluster analysis. Many traditional techniques for one-dimensional problems have been proven inadequate for high-dimensional or mixed type datasets due to the data sparseness and attribute redundancy. In this paper we propose a graph-based clustering method for multidimensional datasets. This novel method has two distinguished features: nonbinary hierarchical tree and the multi-membership clusters. The nonbinary hierarchical tree clearly highlights meaningful clusters, while the multimembership feature may provide more useful service strategies. Experimental results on the customer relationship management confirm the effectiveness of the new method.

  6. Modeling Epidemics Spreading on Social Contact Networks.

    Science.gov (United States)

    Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua

    2015-09-01

    Social contact networks and the way people interact with each other are the key factors that impact on epidemics spreading. However, it is challenging to model the behavior of epidemics based on social contact networks due to their high dynamics. Traditional models such as susceptible-infected-recovered (SIR) model ignore the crowding or protection effect and thus has some unrealistic assumption. In this paper, we consider the crowding or protection effect and develop a novel model called improved SIR model. Then, we use both deterministic and stochastic models to characterize the dynamics of epidemics on social contact networks. The results from both simulations and real data set conclude that the epidemics are more likely to outbreak on social contact networks with higher average degree. We also present some potential immunization strategies, such as random set immunization, dominating set immunization, and high degree set immunization to further prove the conclusion.

  7. Social networking: a matter of character?

    NARCIS (Netherlands)

    Vieth, Marius N.; Kommers, Petrus A.M.

    2014-01-01

    Over the last couple of years, online social networks such as Facebook have tremendously grown in popularity, especially among students. The technological advancements proceed faster than the understanding of the psychological factors behind this development. While motivations and gratifications

  8. Social networking mining, visualization, and security

    CERN Document Server

    Dehuri, Satchidananda; Wang, Gi-Nam

    2014-01-01

    With the proliferation of social media and on-line communities in networked world a large gamut of data has been collected and stored in databases. The rate at which such data is stored is growing at a phenomenal rate and pushing the classical methods of data analysis to their limits. This book presents an integrated framework of recent empirical and theoretical research on social network analysis based on a wide range of techniques from various disciplines like data mining, social sciences, mathematics, statistics, physics, network science, machine learning with visualization techniques, and security. The book illustrates the potential of multi-disciplinary techniques in various real life problems and intends to motivate researchers in social network analysis to design more effective tools by integrating swarm intelligence and data mining.  

  9. Social Support and Social Networks in COPD: A Scoping Review.

    Science.gov (United States)

    Barton, Christopher; Effing, Tanya W; Cafarella, Paul

    2015-01-01

    A scoping review was conducted to determine the size and nature of the evidence describing associations between social support and networks on health, management and clinical outcomes amongst patients with COPD. Searches of PubMed, PsychInfo and CINAHL were undertaken for the period 1966-December 2013. A descriptive synthesis of the main findings was undertaken to demonstrate where there is current evidence for associations between social support, networks and health outcomes, and where further research is needed. The search yielded 318 papers of which 287 were excluded after applying selection criteria. Two areas emerged in which there was consistent evidence of benefit of social support; namely mental health and self-efficacy. There was inconsistent evidence for a relationship between perceived social support and quality of life, physical functioning and self-rated health. Hospital readmission was not associated with level of perceived social support. Only a small number of studies (3 articles) have reported on the social network of individuals with COPD. There remains a need to identify the factors that promote and enable social support. In particular, there is a need to further understand the characteristics of social networks within the broader social structural conditions in which COPD patients live and manage their illness.

  10. HIV/AIDS, social capital, and online social networks.

    Science.gov (United States)

    Drushel, Bruce E

    2013-01-01

    The prospects for online social networks as sites of information-gathering and affiliation for persons with AIDS and others concerned about HIV/AIDS not only represent the latest development in a trend toward circumventing traditional media and official information sources, but also may offer hope for a revitalization of HIV/AIDS discourse in the public sphere. This article provides an overview of three decades of information-seeking on the pandemic and its social and personal implications, as well as case studies of three examples of social networking surrounding HIV/AIDS. It finds preliminary evidence of the formation of strong and weak ties as described in Social Network Theory and suggests that the online accumulation of social capital by opinion leaders could facilitate dissemination of messages on HIV/AIDS awareness and testing.

  11. Online Social Networking: A Primer for Radiology

    OpenAIRE

    Prasanna, Prasanth M.; Seagull, F. Jacob; Nagy, Paul

    2011-01-01

    Online social networking is an immature, but rapidly evolving industry of web-based technologies that allow individuals to develop online relationships. News stories populate the headlines about various websites which can facilitate patient and doctor interaction. There remain questions about protecting patient confidentiality and defining etiquette in order to preserve the doctor/patient relationship and protect physicians. How much social networking-based communication or other forms of E-c...

  12. Returns to Social Network Capital among Traders

    OpenAIRE

    Marcel Fafchamps; Bart Minten

    2000-01-01

    Using data on agricultural traders in Madagascar, this paper shows that social network capital has a large effect on firm productivity. Better connected traders have significantly larger sales and value added than less connected traders after controlling for physical and human inputs as well as for entrepreneur characteristics. The analysis indicates that three dimensions of social network capital should be distinguished: relationships with other traders, which among other things help firms e...

  13. The social brain network and autism.

    Science.gov (United States)

    Misra, Vivek

    2014-04-01

    Available research data in Autism suggests the role of a network of brain areas, often known as the 'social brain'. Recent studies highlight the role of genetic mutations as underlying patho-mechanism in Autism. This mini review, discusses the basic concepts behind social brain networks, theory of mind and genetic factors associated with Autism. It critically evaluates and explores the relationship between the behavioral outcomes and genetic factors providing a conceptual framework for understanding of autism.

  14. Crawling Facebook for Social Network Analysis Purposes

    OpenAIRE

    Catanese, Salvatore A.; De Meo, Pasquale; Ferrara, Emilio; Fiumara, Giacomo; Provetti, Alessandro

    2011-01-01

    We describe our work in the collection and analysis of massive data describing the connections between participants to online social networks. Alternative approaches to social network data collection are defined and evaluated in practice, against the popular Facebook Web site. Thanks to our ad-hoc, privacy-compliant crawlers, two large samples, comprising millions of connections, have been collected; the data is anonymous and organized as an undirected graph. We describe a set of tools that w...

  15. Conversation Analysis on Social Networking Sites

    OpenAIRE

    Belkaroui , Rami; Faiz , Rim; Elkhlifi , Aymen

    2014-01-01

    International audience; With the explosion of Web 2.0, people are becoming more communicative through expansion of services and multi-platform applications such as microblogs, forums and social networks which establishes social and collabora-tive backgrounds. These services can be seen as very large information repository containing millions of text messages usually organized into complex networks involving users interacting with each other at specific times. Several works focused only to ret...

  16. DEPENDENCE ON SOCIAL NETWORKING SITES IN ADOLESCENTS

    OpenAIRE

    Ranjith; Santosh; Amita Rao; Ramgopal; Ashvij

    2016-01-01

    BACKGROUND Social Networking Sites (SNSs) are “web-based services” that allow individuals to: (1) Construct a public or semi-public profile within a bounded system, (2) Articulate a list of other users with whom they share a connection, and (3) View and traverse their list of connections and those made by others within the system.” Social networking sites like Facebook, WhatsApp, Snapchat, Twitter, etc. are virtual communities where users can create individual public profiles,...

  17. Binary Classification Method of Social Network Users

    Directory of Open Access Journals (Sweden)

    I. A. Poryadin

    2017-01-01

    Full Text Available The subject of research is a binary classification method of social network users based on the data analysis they have placed. Relevance of the task to gain information about a person by examining the content of his/her pages in social networks is exemplified. The most common approach to its solution is a visual browsing. The order of the regional authority in our country illustrates that its using in school education is needed. The article shows restrictions on the visual browsing of pupil’s pages in social networks as a tool for the teacher and the school psychologist and justifies that a process of social network users’ data analysis should be automated. Explores publications, which describe such data acquisition, processing, and analysis methods and considers their advantages and disadvantages. The article also gives arguments to support a proposal to study the classification method of social network users. One such method is credit scoring, which is used in banks and credit institutions to assess the solvency of clients. Based on the high efficiency of the method there is a proposal for significant expansion of its using in other areas of society. The possibility to use logistic regression as the mathematical apparatus of the proposed method of binary classification has been justified. Such an approach enables taking into account the different types of data extracted from social networks. Among them: the personal user data, information about hobbies, friends, graphic and text information, behaviour characteristics. The article describes a number of existing methods of data transformation that can be applied to solve the problem. An experiment of binary gender-based classification of social network users is described. A logistic model obtained for this example includes multiple logical variables obtained by transforming the user surnames. This experiment confirms the feasibility of the proposed method. Further work is to define a system

  18. The Commercial Utilization of Social Networks

    OpenAIRE

    Adlaf, Petr

    2011-01-01

    The presented bachelor's thesis deals with advertisement. It answers the question of what advertisement is, why firms use advertisement and what its benefits are. It concentrates especially on Internet advertisement presented through social networks. These social networks have come to occupy a significant position on the Internet during the last five years and offer new possibilities in terms of creating advertising campaigns (Hypertargeting). The thesis presents the division and comparison o...

  19. Jana: Confidential Communications on Social Networks

    Science.gov (United States)

    2017-08-09

    consuming phone resources and privacy leakage ?” We address this challenge via an extensive user study. Next, we ask “How can we detect background apps...not support secret group communications. Furthermore, access to such social networks via mobile platforms raises a series of concerns like leakage of...not support secret group communications. Furthermore, access to such social networks via mobile platforms raises a series of concerns like leakage of

  20. Marketing Impact on Diffusion in Social Networks

    OpenAIRE

    Naumov, Pavel; Tao, Jia

    2016-01-01

    The paper proposes a way to add marketing into the standard threshold model of social networks. Within this framework, the paper studies logical properties of the influence relation between sets of agents in social networks. Two different forms of this relation are considered: one for promotional marketing and the other for preventive marketing. In each case a sound and complete logical system describing properties of the influence relation is proposed. Both systems could be viewed as extensi...

  1. Multilayer Brokerage in Geo-Social Networks

    OpenAIRE

    Hristova, Desislava; Panzarasa, Pietro; Mascolo, Cecilia

    2016-01-01

    This is a metadata record relating to an article that cannot be shared due to publisher copyright. Open network structures and brokerage positions have long been seen as playing a crucial role in sustaining social capital and competitive advantage. The degree to which individuals intermediate between otherwise disconnected others can differ across online and offline social networks. For example, users may broker online between two others who then exchange offline the i...

  2. Multimedia Information Networks in Social Media

    Science.gov (United States)

    Cao, Liangliang; Qi, Guojun; Tsai, Shen-Fu; Tsai, Min-Hsuan; Pozo, Andrey Del; Huang, Thomas S.; Zhang, Xuemei; Lim, Suk Hwan

    The popularity of personal digital cameras and online photo/video sharing community has lead to an explosion of multimedia information. Unlike traditional multimedia data, many new multimedia datasets are organized in a structural way, incorporating rich information such as semantic ontology, social interaction, community media, geographical maps, in addition to the multimedia contents by themselves. Studies of such structured multimedia data have resulted in a new research area, which is referred to as Multimedia Information Networks. Multimedia information networks are closely related to social networks, but especially focus on understanding the topics and semantics of the multimedia files in the context of network structure. This chapter reviews different categories of recent systems related to multimedia information networks, summarizes the popular inference methods used in recent works, and discusses the applications related to multimedia information networks. We also discuss a wide range of topics including public datasets, related industrial systems, and potential future research directions in this field.

  3. Brand communities embedded in social networks.

    Science.gov (United States)

    Zaglia, Melanie E

    2013-02-01

    Brand communities represent highly valuable marketing, innovation management, and customer relationship management tools. However, applying successful marketing strategies today, and in the future, also means exploring and seizing the unprecedented opportunities of social network environments. This study combines these two social phenomena which have largely been researched separately, and aims to investigate the existence, functionality and different types of brand communities within social networks. The netnographic approach yields strong evidence of this existence; leading to a better understanding of such embedded brand communities, their peculiarities, and motivational drivers for participation; therefore the findings contribute to theory by combining two separate research streams. Due to the advantages of social networks, brand management is now able to implement brand communities with less time and financial effort; however, choosing the appropriate brand community type, cultivating consumers' interaction, and staying tuned to this social engagement are critical factors to gain anticipated brand outcomes.

  4. Social networks, big data and transport planning

    Energy Technology Data Exchange (ETDEWEB)

    Ruiz Sanchez, T.; Lidon Mars Aicart, M. del; Arroyo Lopez, M.R.; Serna Nocedal, A.

    2016-07-01

    The characteristics of people who are related or tied to each individual affects her activitytravel behavior. That influence is especially associated to social and recreational activities, which are increasingly important. Collecting high quality data from those social networks is very difficult, because respondents are asked about their general social life, which is most demanding to remember that specific facts. On the other hand, currently there are different potential sources of transport data, which is characterized by the huge amount of information available, the velocity with it is obtained and the variety of format in which is presented. This sort of information is commonly known as Big Data. In this paper we identify potential sources of social network related big data that can be used in Transport Planning. Then, a review of current applications in Transport Planning is presented. Finally, some future prospects of using social network related big data are highlighted. (Author)

  5. Information diffusion in structured online social networks

    Science.gov (United States)

    Li, Pei; Zhang, Yini; Qiao, Fengcai; Wang, Hui

    2015-05-01

    Nowadays, due to the word-of-mouth effect, online social networks have been considered to be efficient approaches to conduct viral marketing, which makes it of great importance to understand the diffusion dynamics in online social networks. However, most research on diffusion dynamics in epidemiology and existing social networks cannot be applied directly to characterize online social networks. In this paper, we propose models to characterize the information diffusion in structured online social networks with push-based forwarding mechanism. We introduce the term user influence to characterize the average number of times that messages are browsed which is incurred by a given type user generating a message, and study the diffusion threshold, above which the user influence of generating a message will approach infinity. We conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of use in understanding the diffusion dynamics in online social networks and also critical for advertisers in viral marketing who want to estimate the user influence before posting an advertisement.

  6. Content Propagation in Online Social Networks

    NARCIS (Netherlands)

    Blenn, N.

    2014-01-01

    This thesis presents methods and techniques to analyze content propagation within online social networks (OSNs) using a graph theoretical approach. Important factors and different techniques to analyze and describe content propagation, starting from the smallest entity in a network, representing a

  7. Segmentation of users of social networking websites

    NARCIS (Netherlands)

    Lorenzo-Romero, C.; Alarcon-del-Amo, M.d.C.; Constantinides, Efthymios

    2012-01-01

    The typology of networked consumers in The Netherlands presented in this study, was based on an online survey and obtained using latent segmentation analysis. This approach is based on the frequency with which users perform different activities, their sociodemographic variables, social networking

  8. Temporal fidelity in dynamic social networks

    DEFF Research Database (Denmark)

    Stopczynski, Arkadiusz; Sapiezynski, Piotr; Pentland, Alex ‘Sandy’

    2015-01-01

    of the network dynamics can be used to inform the process of measuring social networks. The details of measurement are of particular importance when considering dynamic processes where minute-to-minute details are important, because collection of physical proximity interactions with high temporal resolution...

  9. Controlling nosocomial infection based on structure of hospital social networks.

    Science.gov (United States)

    Ueno, Taro; Masuda, Naoki

    2008-10-07

    Nosocomial infection (i.e. infection in healthcare facilities) raises a serious public health problem, as implied by the existence of pathogens characteristic to healthcare facilities such as methicillin-resistant Staphylococcus aureus and hospital-mediated outbreaks of influenza and severe acute respiratory syndrome. For general communities, epidemic modeling based on social networks is being recognized as a useful tool. However, disease propagation may occur in a healthcare facility in a manner different from that in a urban community setting due to different network architecture. We simulate stochastic susceptible-infected-recovered dynamics on social networks, which are based on observations in a hospital in Tokyo, to explore effective containment strategies against nosocomial infection. The observed social networks in the hospital have hierarchical and modular structure in which dense substructure such as departments, wards, and rooms, are globally but only loosely connected, and do not reveal extremely right-skewed distributions of the number of contacts per individual. We show that healthcare workers, particularly medical doctors, are main vectors (i.e. transmitters) of diseases on these networks. Intervention methods that restrict interaction between medical doctors and their visits to different wards shrink the final epidemic size more than intervention methods that directly protect patients, such as isolating patients in single rooms. By the same token, vaccinating doctors with priority rather than patients or nurses is more effective. Finally, vaccinating individuals with large betweenness centrality (frequency of mediating connection between pairs of individuals along the shortest paths) is superior to vaccinating ones with large connectedness to others or randomly chosen individuals, which was suggested by previous model studies.

  10. The Nature Terrorism Reports on Social Networks

    Directory of Open Access Journals (Sweden)

    James Okolie-Osemene

    2015-12-01

    Full Text Available As new tools of communication, an in-depth study of social networking in the era of global terrorism is attempted in this article. This emerging tradition of information sharing is driven by social media technology which has greatly revolutionalised communication in all sectors. The article explored the information sharing relevance of new technologies in the age of terrorism and counterterrorism. It focused on how social networks are increasingly utilised by different groups. In terms of methodology, the study extracted and utilised positive, negative and neutral posts, updates, tweets and reports on social networks through different individual and organisational media accounts and blogs, and analysed the data qualitatively. Findings show that despite being used by extremist groups in promoting their political agenda, social networks are also useful in promoting positive perceptions that society has about Muslims in the era of terrorism, emphasising that Muslims are not terrorists. Through the instrumentality of social media, users are able to map the trends of terrorism and responses from stakeholders in government and security sector in curbing the menace. Given their capacity to reach a wider audience, breaking cultural and religious barriers, social networks serve as early warning signs and make it possible for people to share new ideas on possible ways of curbing the proliferation of terrorist organisations.

  11. SOCIAL NETWORKS BETWEEN ICTS AND MORAL DECADENCE

    Directory of Open Access Journals (Sweden)

    Domingo Alarcón Ortiz

    2013-07-01

    Full Text Available The paradox of social networks in organizations is that they are a very important means of formation, training, update, information and communication, but also represent a symptom of cultural decay, because with them have been provided and processes of disinformation uncontrolled distribution of malicious information, which is assaulted by people. The abuse as to upload information indiscriminately leads to pathological, anti-social and cynical time’s behaviors. As many users of social networks does not assume a code of ethics according to social needs, then its limits of performance in terms of dignity and self-respect will not operate, constitute a serious social threat, against which the appropriate response has not been generated.  To participate in social networks, people end up exposing itself to that your privacy was hurt with impunity and thereby will limit or annul the opportunity to defend their dignity, turning them into a set of highly vulnerable entities. But as there is social by joining the network pressure, the question is it worth being in these networks? If you want to stay informed and share information, raises the dilemma of to where it can and should go.

  12. Measuring Social Capital in Virtual Social Networks; Introducing Workable Indices

    Directory of Open Access Journals (Sweden)

    Hamid Abdollahian

    2013-12-01

    Full Text Available This paper will attempt to offer a set of indicators that together construct a model which will help to measure social capital among users of social networks. The world is now experiencing some new changes that are affecting conceptual equations in social sciences, two of which are of our concern here: 1- the concept of social capital that has opened its way into epistemological basis of social sciences, and; 2- the world has welcomed the birth and development of social networks in our daily life, affecting many aspects of social actions. There is Facebook from among a handful of social networks that has reached the threshold of international networking capacity with roughly one billion users. We will use Robert Putnam's theory of social capital alongside Frank's methodological innovation regarding measuring tools of social capital in order to create a marriage between these two as well as to address a yet more problematizing issue, i.e., how to measure social capital of the Facebook users. Accordingly the paper will focus on Facebook as the field of research and will introduce triangulation approach that we used in order to come up with the set of indicators. Participatory observation and online survey were used as constructing elements of triangulation approach so to generate the necessary data for the above purpose. At first, we used participatory observation through which 14 targeted samples were selected and whatever they had in their profile in Facebook were collected and analyzed. This analysis helped us to construct our questionnaire which was launched through Google docs. In the end, some 218 respondent returned their completed questionnaires. The final stage of analysis consisted of finding out how we can use the results to offer a new tool for measuring social capital of Facebook users. The research findings indicated that there are 10 indicators which should be put together if social capital is to be properly measured.

  13. Social networks and their influence over the social consciousness forming

    Directory of Open Access Journals (Sweden)

    A. G. Ananeva

    2011-09-01

    Full Text Available The article describes the analysis of social network influence on social consciousness forming. The examples of connection between international politic courses and events and blogosrheres’ virtual activity are given. Due to the analysis made, authors point at negative consequences following the information wars’ dissemination.

  14. Data Storage for Social Networks A Socially Aware Approach

    CERN Document Server

    Tran, Duc A

    2012-01-01

    Evidenced by the success of Facebook, Twitter, and LinkedIn, online social networks (OSNs) have become ubiquitous, offering novel ways for people to access information and communicate with each other. As the increasing popularity of social networking is undeniable, scalability is an important issue for any OSN that wants to serve a large number of users. Storing user data for the entire network on a single server can quickly lead to a bottleneck, and, consequently, more servers are needed to expand storage capacity and lower data request traffic per server. Adding more servers is just one step

  15. Social media networking: Facebook and Twitter.

    Science.gov (United States)

    Schneider, Andrew; Jackson, Rem; Baum, Neil

    2010-01-01

    The new wave of marketing and practice promotion will include social media networking. This article will discuss Facebook and Twitter. After reading this article you, will have an understanding of these two important aspects of social media and how you might use Facebook and Twitter in your practice to enhance your communication with your existing patients and attract new patients.

  16. Spatial and Social Networks in Organizational Innovation

    Science.gov (United States)

    Wineman, Jean D.; Kabo, Felichism W.; Davis, Gerald F.

    2009-01-01

    Research on the enabling factors of innovation has focused on either the social component of organizations or on the spatial dimensions involved in the innovation process. But no one has examined the aggregate consequences of the link from spatial layout, to social networks, to innovation. This project enriches our understanding of how innovation…

  17. Online Social Networking: Usage in Adolescents

    Science.gov (United States)

    Raju, Nevil Johnson; Valsaraj, Blessy Prabha; Noronha, Judith

    2015-01-01

    Online social networking (OSN) has played a significant role on the relationship among college students. It is becoming a popular medium for socializing online and tools to facilitate friendship. Young adults and adolescents are the most prolific users of OSN sites. The frequent use of OSN sites results in addiction toward these sites and…

  18. College Students' Social Networking Experiences on Facebook

    Science.gov (United States)

    Pempek, Tiffany A.; Yermolayeva, Yevdokiya A.; Calvert, Sandra L.

    2009-01-01

    Millions of contemporary young adults use social networking sites. However, little is known about how much, why, and how they use these sites. In this study, 92 undergraduates completed a diary-like measure each day for a week, reporting daily time use and responding to an activities checklist to assess their use of the popular social networking…

  19. Facebook, Social Networking, and Business Education

    Science.gov (United States)

    Taylor, Steven A.; Mulligan, Jamie R.; Ishida, Chiharu

    2012-01-01

    Brown (2012) asserts that faculty perceptions of Web 2.0 for teaching will influence its adoption. For example, social media's influence on educational delivery is growing (Hrastinski and Dennon 2012). Zulu et al. (2011) note that business educators are only beginning to understand social networking related to education. We report an exploratory…

  20. Knowledge Strategies in Using Social Networks

    Directory of Open Access Journals (Sweden)

    Contantin BRĂTIANU

    2013-05-01

    Full Text Available Knowledge strategy selection is a multiple criteria decision-making (MCDM problem, and requires adequate methods to solve it appropriately. Knowledge strategies are also intrinsically linked to individuals and their ability to comprehend the world and leverage their intellectual assets to respond e!ectively to a fast changing environment. the essential features of social networking sites include but are not limited to: blogging, grouping, networking and instant messaging. Since the social networks facilitate communication and interaction among users, there is a continuous need of researches to examine what are the motives that a!ect the acceptance of usage of the social networks. This study aims at examining the role of the knowledge strategies that individuals employ in using social networks with respect to the overall objective of increasing the knowledge level. For this purpose we have used the Analytic Hierarchy Process (AHP mathematical model since it allows us a structuring of the overall objective on the main components. For the present research we considered a structure composed of three levels: L1 – the purpose of networking, L2 – strategies used to achieve that purpose, and L3 – activities needed for strategies implementation. At the upper level (L1, the main objective of a person in using social networks is to increase its knowledge level. To obtain the aforementioned objective we considered for the second level (L2 the following strategies: S1 – to learn from other persons; S2 – to make new friends; S3 – to increase the personal experience and visibility. the implementation of these strategies is realized through the following activities considered at the third hierarchy level (L3: A1– joining general social networks (e.g. Facebook, Google+, MySpace, Hi5 etc.; A2– joining professional social networks (e.g. LinkedIn etc.; A3– creating a personal blog (e.g. Blogster, Wordpress etc.; A4– joining online communities of

  1. Neighborhood social capital and crime victimization: comparison of spatial regression analysis and hierarchical regression analysis.

    Science.gov (United States)

    Takagi, Daisuke; Ikeda, Ken'ichi; Kawachi, Ichiro

    2012-11-01

    Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g., Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a spatial Durbin model with an inverse-distance weighting matrix that assigned each respondent a unique level of "exposure" to social capital based on all other residents' perceptions. The study is based on a postal questionnaire sent to 20-69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the spatial Durbin model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan. Copyright

  2. Social Influence on Information Technology Adoption and Sustained Use in Healthcare: A Hierarchical Bayesian Learning Method Analysis

    Science.gov (United States)

    Hao, Haijing

    2013-01-01

    Information technology adoption and diffusion is currently a significant challenge in the healthcare delivery setting. This thesis includes three papers that explore social influence on information technology adoption and sustained use in the healthcare delivery environment using conventional regression models and novel hierarchical Bayesian…

  3. Online social networking: a primer for radiology.

    Science.gov (United States)

    Prasanna, Prasanth M; Seagull, F Jacob; Nagy, Paul

    2011-10-01

    Online social networking is an immature, but rapidly evolving industry of web-based technologies that allow individuals to develop online relationships. News stories populate the headlines about various websites which can facilitate patient and doctor interaction. There remain questions about protecting patient confidentiality and defining etiquette in order to preserve the doctor/patient relationship and protect physicians. How much social networking-based communication or other forms of E-communication is effective? What are the potential benefits and pitfalls of this form of communication? Physicians are exploring how social networking might provide a forum for interacting with their patients, and advance collaborative patient care. Several organizations and institutions have set forth policies to address these questions and more. Though still in its infancy, this form of media has the power to revolutionize the way physicians interact with their patients and fellow health care workers. In the end, physicians must ask what value is added by engaging patients or other health care providers in a social networking format. Social networks may flourish in health care as a means of distributing information to patients or serve mainly as support groups among patients. Physicians must tread a narrow path to bring value to interactions in these networks while limiting their exposure to unwanted liability.

  4. Social network for people with food intolerances

    OpenAIRE

    Ponce Alboques, Judit

    2017-01-01

    The concepts behind “social networking” are nothing new – humans have always been social beings, looking for ways to connect and interact with each other – but they have taken a new meaning in today's society. Social network sites are a phenomenon of great importance; many people feel better interacting online. This fact, together with the recent increase of people with food allergies and intolerances, have an interesting connection. In recent years the healthy life style has become fashionab...

  5. Undermining and Strengthening Social Networks through Network Modification

    Science.gov (United States)

    Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

    2016-10-01

    Social networks have well documented effects at the individual and aggregate level. Consequently it is often useful to understand how an attempt to influence a network will change its structure and consequently achieve other goals. We develop a framework for network modification that allows for arbitrary objective functions, types of modification (e.g. edge weight addition, edge weight removal, node removal, and covariate value change), and recovery mechanisms (i.e. how a network responds to interventions). The framework outlined in this paper helps both to situate the existing work on network interventions but also opens up many new possibilities for intervening in networks. In particular use two case studies to highlight the potential impact of empirically calibrating the objective function and network recovery mechanisms as well as showing how interventions beyond node removal can be optimised. First, we simulate an optimal removal of nodes from the Noordin terrorist network in order to reduce the expected number of attacks (based on empirically predicting the terrorist collaboration network from multiple types of network ties). Second, we simulate optimally strengthening ties within entrepreneurial ecosystems in six developing countries. In both cases we estimate ERGM models to simulate how a network will endogenously evolve after intervention.

  6. Social Network Supported Process Recommender System

    Directory of Open Access Journals (Sweden)

    Yanming Ye

    2014-01-01

    Full Text Available Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced.

  7. Social network supported process recommender system.

    Science.gov (United States)

    Ye, Yanming; Yin, Jianwei; Xu, Yueshen

    2014-01-01

    Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced.

  8. Myths on Bi-direction Communication of Web 2.0 Based Social Networks: Is Social Network Truly Interactive?

    Science.gov (United States)

    2011-03-10

    more and more social interactions are happening on the on-line. Especially recent uptake of the social network sites (SNSs), such as Facebook (http...Smart phones • Live updates within social networks • Facebook & Twitters Solution: WebMon for Risk Management Need for New WebMon for Social Networks ...Title: Myths on bi-direction communication of Web 2.0 based social networks : Is social network truly interactive

  9. Community Structure in Online Collegiate Social Networks

    Science.gov (United States)

    Traud, Amanda; Kelsic, Eric; Mucha, Peter; Porter, Mason

    2009-03-01

    Online social networking sites have become increasingly popular with college students. The networks we studied are defined through ``friendships'' indicated by Facebook users from UNC, Oklahoma, Caltech, Georgetown, and Princeton. We apply the tools of network science to study the Facebook networks from these five different universities at a single point in time. We investigate each single-institution network's community structure, which we obtain through partitioning the graph using an eigenvector method. We use both graphical and quantitative tools, including pair-counting methods, which we interpret through statistical analysis and permutation tests to measure the correlations between the network communities and a set of characteristics given by each user (residence, class year, major, and high school). We also analyze the single gender subsets of these networks, and the impact of missing demographical data. Our study allows us to compare the online social networks for the five schools as well as infer differences in offline social interactions. At the schools studied, we were able to define which characteristics of the Facebook users correlate best with friendships.

  10. A framework for online social networking features

    Directory of Open Access Journals (Sweden)

    Mohsen Shafiei Nikabadi

    2014-06-01

    Full Text Available Social networks form a basis for maintaining social contacts, finding users with common interests, creating local content and sharing information. Recently networks have created a fundamental framework for analyzing and modeling the complex systems. Users' behavior studies and evaluates the system performance and leads to better planning and implementation of advertising policies on the web sites. Therefore, this study offers a framework for online social networks' characteristics. In terms of objective, this survey is practical descriptive. Sampling has been done among 384 of graduate students who have good experiences of membership in online social network. Confirmatory factor analysis is used to evaluate the validity of variables in research model. Characteristics of online social networks are defined based on six components and framework's indexes are analyzed through factor analysis. The reliability is calculated separately for each dimension and since they are all above 0.7, the reliability of the study can be confirmed. According to our research results, in terms of size, the number of people who apply for membership in various online social networking is an important index. In terms of individual preference to connect with, people who are relative play essential role in social network development. In terms of homogeneity variable, the number of people who visit their friends’ pages is important for measuring frequency variable. In terms of frequency, the use of entertainment and recreation services is more important index. In terms of proximity, being in the same city is a more important index and index of creating a sense of belonging and confidence is more important for measuring reciprocity variable.

  11. A comparative performance evaluation of intrusion detection techniques for hierarchical wireless sensor networks

    Directory of Open Access Journals (Sweden)

    H.H. Soliman

    2012-11-01

    Full Text Available An explosive growth in the field of wireless sensor networks (WSNs has been achieved in the past few years. Due to its important wide range of applications especially military applications, environments monitoring, health care application, home automation, etc., they are exposed to security threats. Intrusion detection system (IDS is one of the major and efficient defensive methods against attacks in WSN. Therefore, developing IDS for WSN have attracted much attention recently and thus, there are many publications proposing new IDS techniques or enhancement to the existing ones. This paper evaluates and compares the most prominent anomaly-based IDS systems for hierarchical WSNs and identifying their strengths and weaknesses. For each IDS, the architecture and the related functionality are briefly introduced, discussed, and compared, focusing on both the operational strengths and weakness. In addition, a comparison of the studied IDSs is carried out using a set of critical evaluation metrics that are divided into two groups; the first one related to performance and the second related to security. Finally based on the carried evaluation and comparison, a set of design principles are concluded, which have to be addressed and satisfied in future research of designing and implementing IDS for WSNs.

  12. Interference mitigation for broadcast in hierarchical cell structure networks: Transmission strategy and area spectral efficiency

    KAUST Repository

    Yang, Yuli

    2014-10-01

    In this paper, a hierarchical cell structure (HCS) is considered, where an access point (AP) broadcasts to local nodes (LNs) over orthogonal frequency subbands within a local cell located in a macrocell. Since the local cell shares the spectrum licensed to the macrocell, a given LN is interfered with by the macrocell user (MU)\\'s transmissions over the same subband. To improve the performance of the AP\\'s broadcast service, a novel transmission strategy is proposed to mitigate the interference from the MU to the LN while achieving diversity gain. For the purpose of performance evaluation, the ergodic capacity of the proposed scheme is quantified, and the corresponding closed-form expression is obtained. By comparing with the traditional transmission scheme, which suffers from MU\\'s interference, illustrative numerical results substantiate that the proposed scheme achieves better performance than the traditional scheme as the MU-LN mean channel power gain is larger than half of the AP-LN mean channel power gain. Subsequently, we develop an optimized network design by maximizing the area spectral efficiency (ASE) of the AP\\'s broadcast in the local cell.

  13. Hierarchical Status Predicts Behavioral Vulnerability and Nucleus Accumbens Metabolic Profile Following Chronic Social Defeat Stress.

    Science.gov (United States)

    Larrieu, Thomas; Cherix, Antoine; Duque, Aranzazu; Rodrigues, João; Lei, Hongxia; Gruetter, Rolf; Sandi, Carmen

    2017-07-24

    Extensive data highlight the existence of major differences in individuals' susceptibility to stress [1-4]. While genetic factors [5, 6] and exposure to early life stress [7, 8] are key components for such neurobehavioral diversity, intriguing observations revealed individual differences in response to stress in inbred mice [9-12]. This raised the possibility that other factors might be critical in stress vulnerability. A key challenge in the field is to identify non-invasively risk factors for vulnerability to stress. Here, we investigated whether behavioral factors, emerging from preexisting dominance hierarchies, could predict vulnerability to chronic stress [9, 13-16]. We applied a chronic social defeat stress (CSDS) model of depression in C57BL/6J mice to investigate the predictive power of hierarchical status to pinpoint which individuals will exhibit susceptibility to CSDS. Given that the high social status of dominant mice would be the one particularly challenged by CSDS, we predicted and found that dominant individuals were the ones showing a strong susceptibility profile as indicated by strong social avoidance following CSDS, while subordinate mice were not affected. Data from 1 H-NMR spectroscopy revealed that the metabolic profile in the nucleus accumbens (NAc) relates to social status and vulnerability to stress. Under basal conditions, subordinates show lower levels of energy-related metabolites compared to dominants. In subordinates, but not dominants, levels of these metabolites were increased after exposure to CSDS. To the best of our knowledge, this is the first study that identifies non-invasively the origin of behavioral risk factors predictive of stress-induced depression-like behaviors associated with metabolic changes. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. The use of electronic communication (social network) by open and ...

    African Journals Online (AJOL)

    The use of electronic communication (social network) by open and distance students, ... ODL students use face book and whatsapps as their preferred social networks. ... networks distract academic studies and it is expensive to use, also more ...

  15. Inferring Trust Relationships in Web-Based Social Networks

    National Research Council Canada - National Science Library

    Golbeck, Jennifer; Hendler, James

    2006-01-01

    The growth of web-based social networking and the properties of those networks have created great potential for producing intelligent software that integrates a user's social network and preferences...

  16. Correlation between hierarchical structure of crystal networks and macroscopic performance of mesoscopic soft materials and engineering principles.

    Science.gov (United States)

    Lin, Naibo; Liu, Xiang Yang

    2015-11-07

    This review examines how the concepts and ideas of crystallization can be extended further and applied to the field of mesoscopic soft materials. It concerns the structural characteristics vs. the macroscopic performance, and the formation mechanism of crystal networks. Although this subject can be discussed in a broad sense across the area of mesoscopic soft materials, our main focus is on supramolecular materials, spider and silkworm silks, and biominerals. First, the occurrence of a hierarchical structure, i.e. crystal network and domain network structures, will facilitate the formation kinetics of mesoscopic phases and boost up the macroscopic performance of materials in some cases (i.e. spider silk fibres). Second, the structure and performance of materials can be correlated in some way by the four factors: topology, correlation length, symmetry/ordering, and strength of association of crystal networks. Moreover, four different kinetic paths of crystal network formation are identified, namely, one-step process of assembly, two-step process of assembly, mixed mode of assembly and foreign molecule mediated assembly. Based on the basic mechanisms of crystal nucleation and growth, the formation of crystal networks, such as crystallographic mismatch (or noncrystallographic) branching (tip branching and fibre side branching) and fibre/polymeric side merging, are reviewed. This facilitates the rational design and construction of crystal networks in supramolecular materials. In this context, the (re-)construction of a hierarchical crystal network structure can be implemented by thermal, precipitate, chemical, and sonication stimuli. As another important class of soft materials, the unusual mechanical performance of spider and silkworm silk fibres are reviewed in comparison with the regenerated silk protein derivatives. It follows that the considerably larger breaking stress and unusual breaking strain of spider silk fibres vs. silkworm silk fibres can be interpreted

  17. CHIMERA: Top-down model for hierarchical, overlapping and directed cluster structures in directed and weighted complex networks

    Science.gov (United States)

    Franke, R.

    2016-11-01

    In many networks discovered in biology, medicine, neuroscience and other disciplines special properties like a certain degree distribution and hierarchical cluster structure (also called communities) can be observed as general organizing principles. Detecting the cluster structure of an unknown network promises to identify functional subdivisions, hierarchy and interactions on a mesoscale. It is not trivial choosing an appropriate detection algorithm because there are multiple network, cluster and algorithmic properties to be considered. Edges can be weighted and/or directed, clusters overlap or build a hierarchy in several ways. Algorithms differ not only in runtime, memory requirements but also in allowed network and cluster properties. They are based on a specific definition of what a cluster is, too. On the one hand, a comprehensive network creation model is needed to build a large variety of benchmark networks with different reasonable structures to compare algorithms. On the other hand, if a cluster structure is already known, it is desirable to separate effects of this structure from other network properties. This can be done with null model networks that mimic an observed cluster structure to improve statistics on other network features. A third important application is the general study of properties in networks with different cluster structures, possibly evolving over time. Currently there are good benchmark and creation models available. But what is left is a precise sandbox model to build hierarchical, overlapping and directed clusters for undirected or directed, binary or weighted complex random networks on basis of a sophisticated blueprint. This gap shall be closed by the model CHIMERA (Cluster Hierarchy Interconnection Model for Evaluation, Research and Analysis) which will be introduced and described here for the first time.

  18. Forecasting building energy consumption with hybrid genetic algorithm-hierarchical adaptive network-based fuzzy inference system

    Energy Technology Data Exchange (ETDEWEB)

    Li, Kangji [Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027 (China); School of Electricity Information Engineering, Jiangsu University, Zhenjiang 212013 (China); Su, Hongye [Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027 (China)

    2010-11-15

    There are several ways to forecast building energy consumption, varying from simple regression to models based on physical principles. In this paper, a new method, namely, the hybrid genetic algorithm-hierarchical adaptive network-based fuzzy inference system (GA-HANFIS) model is developed. In this model, hierarchical structure decreases the rule base dimension. Both clustering and rule base parameters are optimized by GAs and neural networks (NNs). The model is applied to predict a hotel's daily air conditioning consumption for a period over 3 months. The results obtained by the proposed model are presented and compared with regular method of NNs, which indicates that GA-HANFIS model possesses better performance than NNs in terms of their forecasting accuracy. (author)

  19. Analysis of Layered Social Networks

    Science.gov (United States)

    2006-09-01

    community. Acta Physica Polonica B, 36(8):2559–2574, 2005. V. N. Parrillo and C. Donoghue. Updating the Borgardus social distance studies: A new...relative agreement opinion dynamics. Physica A, 343:725–738, 2004. C. Anderson, O. P. John, D. Keltner, and A. M. Kring. Who attains social sta- tus...and information flow. Physica A, 316:695–708, 2002. 336 M. J. Lovaglia, R. Willer, and L. Troyer. Power, status, and collective action: Devel- oping

  20. Optimization-Based Selection of Influential Agents in a Rural Afghan Social Network

    Science.gov (United States)

    2010-06-01

    nonlethal targeting model, a nonlinear programming ( NLP ) optimization formulation that identifies the k US agent assignment strategy producing the greatest...leader social network, and 3) the nonlethal targeting model, a nonlinear programming ( NLP ) optimization formulation that identifies the k US agent...NATO Coalition in Afghanistan. 55 for Afghanistan ( [54], [31], [48], [55], [30]). While Arab tribes tend to be more hierarchical, Pashtun tribes are

  1. Competing opinion diffusion on social networks.

    Science.gov (United States)

    Hu, Haibo

    2017-11-01

    Opinion competition is a common phenomenon in real life, such as with opinions on controversial issues or political candidates; however, modelling this competition remains largely unexplored. To bridge this gap, we propose a model of competing opinion diffusion on social networks taking into account degree-dependent fitness or persuasiveness. We study the combined influence of social networks, individual fitnesses and attributes, as well as mass media on people's opinions, and find that both social networks and mass media act as amplifiers in opinion diffusion, the amplifying effect of which can be quantitatively characterized. We analytically obtain the probability that each opinion will ultimately pervade the whole society when there are no committed people in networks, and the final proportion of each opinion at the steady state when there are committed people in networks. The results of numerical simulations show good agreement with those obtained through an analytical approach. This study provides insight into the collective influence of individual attributes, local social networks and global media on opinion diffusion, and contributes to a comprehensive understanding of competing diffusion behaviours in the real world.

  2. Social Networks and Political Parties in Chile

    Directory of Open Access Journals (Sweden)

    Adler Lomnitz, Larissa

    2002-09-01

    Full Text Available This paper describes the origin and evolution of two Chilean political parties (the Radical Party and the Christian Democrat Party through the analysis of the social networks that originated and composed them. The aim of this study is to propose a model of national political cultures on the basis of the structure of social networks related to power and of the symbol system, which legitimizes it. The structure of social networks, horizontal and vertical, are based on reciprocal or redistributive forms of exchange, on what is being exchanged and on the articulation between networks. In every society there are symmetrical and asymmetrical exchanges, which produce horizontal and vertical networks. These networks interact among themselves to form the social fabric. The dominance of some over others and how they combine, delineate the character of the political culture (authoritarian vs. egalitarian. Chile is a multiparty country within which there are cohorts of horizontal groups of friends, who informally exercise a central control over their members and create invisible boundaries setting them apart from others, in which leadership is under constrains. The result is both a strong presidential system based on an almost fanatic legitimacy, combined with factionalism and a strong parliamentary system.

  3. Community Core Evolution in Mobile Social Networks

    Directory of Open Access Journals (Sweden)

    Hao Xu

    2013-01-01

    Full Text Available Community detection in social networks attracts a lot of attention in the recent years. Existing methods always depict the relationship of two nodes using the temporary connection. However, these temporary connections cannot be fully recognized as the real relationships when the history connections among nodes are considered. For example, a casual visit in Facebook cannot be seen as an establishment of friendship. Hence, our question is the following: how to cluster the real friends in mobile social networks? In this paper, we study the problem of detecting the stable community core in mobile social networks. The cumulative stable contact is proposed to depict the relationship among nodes. The whole process is divided into timestamps. Nodes and their connections can be added or removed at each timestamp, and historical contacts are considered when detecting the community core. Also, community cores can be tracked through the incremental computing, which can help to recognize the evolving of community structure. Empirical studies on real-world social networks demonstrate that our proposed method can effectively detect stable community cores in mobile social networks.

  4. Community core evolution in mobile social networks.

    Science.gov (United States)

    Xu, Hao; Xiao, Weidong; Tang, Daquan; Tang, Jiuyang; Wang, Zhenwen

    2013-01-01

    Community detection in social networks attracts a lot of attention in the recent years. Existing methods always depict the relationship of two nodes using the temporary connection. However, these temporary connections cannot be fully recognized as the real relationships when the history connections among nodes are considered. For example, a casual visit in Facebook cannot be seen as an establishment of friendship. Hence, our question is the following: how to cluster the real friends in mobile social networks? In this paper, we study the problem of detecting the stable community core in mobile social networks. The cumulative stable contact is proposed to depict the relationship among nodes. The whole process is divided into timestamps. Nodes and their connections can be added or removed at each timestamp, and historical contacts are considered when detecting the community core. Also, community cores can be tracked through the incremental computing, which can help to recognize the evolving of community structure. Empirical studies on real-world social networks demonstrate that our proposed method can effectively detect stable community cores in mobile social networks.

  5. Transparent conducting films of hierarchically nanostructured polyaniline networks on flexible substrates for high-performance gas sensors.

    Science.gov (United States)

    Bai, Shouli; Sun, Chaozheng; Wan, Pengbo; Wang, Cheng; Luo, Ruixian; Li, Yaping; Liu, Junfeng; Sun, Xiaoming

    2015-01-21

    Transparent chemical gas sensors are assembled from a transparent conducting film of hierarchically nanostructured polyaniline (PANI) networks fabricated on a flexible PET substrate, by coating silver nanowires (Ag NWs) followed by the in situ polymerization of aniline near the sacrificial Ag NW template. The sensor exhibits enhanced gas sensing performance at room temperature in both sensitivity and selectivity to NH3 compared to pure PANI film. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Social networking for adolescents with severe haemophilia.

    Science.gov (United States)

    Khair, K; Holland, M; Carrington, S

    2012-05-01

    Access to modern treatments allows adolescents with haemophilia to manage their haemophilia at home, with improved treatment outcomes and quality of life, but has reduced peer support and the potential for experiential learning from older peers. Social networking, aided by modern communication technologies, may offer health benefits through peer support. We sought to assess whether or not disease-specific social networking could benefit adolescents with severe haemophilia. A total of 150 adolescents (aged 10-18) with severe haemophilia A or B from 11 UK treatment centres or those who had attended focus groups to explore the potential for a social network designed specifically for their use were surveyed. Teenage boys with severe haemophilia in the UK who responded to an online and paper questionnaire (n = 47; 31% response rate) rarely knew of or socialized with others with haemophilia outside their families. Two-thirds of respondents said they would like to meet others. For 70% of boys, parents were the major source of information about haemophilia, yet more than half said they often had trouble finding answers to their questions. These boys frequently used online social networks to chat with friends. Adolescents with severe haemophilia frequently have limited contact with others and many wish to have greater contact. They may benefit from peer support and experiential learning gained through online social networking. The SixVibe restricted access social network is to be launched in 2011. It includes features designed to promote and facilitate the development of peer-to peer disease management skills for adolescents with severe haemophilia. © 2011 Blackwell Publishing Ltd.

  7. Origin of Peer Influence in Social Networks

    Science.gov (United States)

    Pinheiro, Flávio L.; Santos, Marta D.; Santos, Francisco C.; Pacheco, Jorge M.

    2014-03-01

    Social networks pervade our everyday lives: we interact, influence, and are influenced by our friends and acquaintances. With the advent of the World Wide Web, large amounts of data on social networks have become available, allowing the quantitative analysis of the distribution of information on them, including behavioral traits and fads. Recent studies of correlations among members of a social network, who exhibit the same trait, have shown that individuals influence not only their direct contacts but also friends' friends, up to a network distance extending beyond their closest peers. Here, we show how such patterns of correlations between peers emerge in networked populations. We use standard models (yet reflecting intrinsically different mechanisms) of information spreading to argue that empirically observed patterns of correlation among peers emerge naturally from a wide range of dynamics, being essentially independent of the type of information, on how it spreads, and even on the class of underlying network that interconnects individuals. Finally, we show that the sparser and clustered the network, the more far reaching the influence of each individual will be.

  8. Social networks, social support and psychiatric symptoms: social determinants and associations within a multicultural community population.

    Science.gov (United States)

    Smyth, Natasha; Siriwardhana, Chesmal; Hotopf, Matthew; Hatch, Stephani L

    2015-07-01

    Little is known about how social networks and social support are distributed within diverse communities and how different types of each are associated with a range of psychiatric symptoms. This study aims to address such shortcomings by: (1) describing the demographic and socioeconomic characteristics of social networks and social support in a multicultural population and (2) examining how each is associated with multiple mental health outcomes. Data is drawn from the South East London Community Health Study; a cross-sectional study of 1,698 adults conducted between 2008 and 2010. The findings demonstrate variation in social networks and social support by socio-demographic factors. Ethnic minority groups reported larger family networks but less perceived instrumental support. Older individuals and migrant groups reported lower levels of particular network and support types. Individuals from lower socioeconomic groups tended to report less social networks and support across the indicators measured. Perceived emotional and instrumental support, family and friend network size emerged as protective factors for common mental disorder, personality dysfunction and psychotic experiences. In contrast, both social networks and social support appear less relevant for hazardous alcohol use. The findings both confirm established knowledge that social networks and social support exert differential effects on mental health and furthermore suggest that the particular type of social support may be important. In contrast, different types of social network appear to impact upon poor mental health in a more uniform way. Future psychosocial strategies promoting mental health should consider which social groups are vulnerable to reduced social networks and poor social support and which diagnostic groups may benefit most.

  9. SDN‐Based Hierarchical Agglomerative Clustering Algorithm for Interference Mitigation in Ultra‐Dense Small Cell Networks

    Directory of Open Access Journals (Sweden)

    Guang Yang

    2018-04-01

    Full Text Available Ultra‐dense small cell networks (UD‐SCNs have been identified as a promising scheme for next‐generation wireless networks capable of meeting the ever‐increasing demand for higher transmission rates and better quality of service. However, UD‐SCNs will inevitably suffer from severe interference among the small cell base stations, which will lower their spectral efficiency. In this paper, we propose a software‐defined networking (SDN‐based hierarchical agglomerative clustering (SDN‐HAC framework, which leverages SDN to centrally control all sub‐channels in the network, and decides on cluster merging using a similarity criterion based on a suitability function. We evaluate the proposed algorithm through simulation. The obtained results show that the proposed algorithm performs well and improves system payoff by 18.19% and 436.34% when compared with the traditional network architecture algorithms and non‐cooperative scenarios, respectively.

  10. Online and Offline Social Networks: Use of Social Networking Sites by Emerging Adults

    Science.gov (United States)

    Subrahmanyam, Kaveri; Reich, Stephanie M.; Waechter, Natalia; Espinoza, Guadalupe

    2008-01-01

    Social networking sites (e.g., MySpace and Facebook) are popular online communication forms among adolescents and emerging adults. Yet little is known about young people's activities on these sites and how their networks of "friends" relate to their other online (e.g., instant messaging) and offline networks. In this study, college students…

  11. Social capital, friendship networks, and youth unemployment.

    Science.gov (United States)

    Hällsten, Martin; Edling, Christofer; Rydgren, Jens

    2017-01-01

    Youth unemployment is a contemporary social problem in many societies. Youths often have limited access to information about jobs and limited social influence, yet little is known about the relationship between social capital and unemployment risk among youth. We study the effect of social capital on unemployment risk in a sample of 19 year olds of Swedish, Iranian, and Yugoslavian origin living in Sweden (N = 1590). We distinguish between two dimensions of social capital: occupational contact networks and friendship networks. First, ego's unemployment is found to be strongly associated with friends' unemployment among individuals of Yugoslavian origins and individuals of Swedish origin, but not Iranian origin. Second, occupational contact networks reduce unemployment risks for all groups, but especially so for Iranians. The effect sizes of the two dimensions are similar and substantial: going from low to high values on these measures is associated with a difference of some 60-70 percent relative difference in unemployment risk. The findings are robust to a number of different model specifications, including a rich set of social origin controls, personality traits, educational performance, friends' characteristics, and friendship network characteristics, as well as controls for geographical employment patterns. A sensitivity simulation shows that homogeneity bias need to be very strong to explain away the effect. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. Security and trust in online social networks

    CERN Document Server

    Carminati, Barbara; Viviani, Marco; Viviani, Marco; Carminati, Barbara

    2013-01-01

    The enormous success and diffusion that online social networks (OSNs) are encountering nowadays is vastly apparent. Users' social interactions now occur using online social media as communication channels; personal information and activities are easily exchanged both for recreational and business purposes in order to obtain social or economic advantages. In this scenario, OSNs are considered critical applications with respect to the security of users and their resources, for their characteristics alone: the large amount of personal information they manage, big economic upturn connected to thei

  13. Spreading paths in partially observed social networks

    Science.gov (United States)

    Onnela, Jukka-Pekka; Christakis, Nicholas A.

    2012-03-01

    Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.

  14. Spreading paths in partially observed social networks.

    Science.gov (United States)

    Onnela, Jukka-Pekka; Christakis, Nicholas A

    2012-03-01

    Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.

  15. Gossip spread in social network Models

    Science.gov (United States)

    Johansson, Tobias

    2017-04-01

    Gossip almost inevitably arises in real social networks. In this article we investigate the relationship between the number of friends of a person and limits on how far gossip about that person can spread in the network. How far gossip travels in a network depends on two sets of factors: (a) factors determining gossip transmission from one person to the next and (b) factors determining network topology. For a simple model where gossip is spread among people who know the victim it is known that a standard scale-free network model produces a non-monotonic relationship between number of friends and expected relative spread of gossip, a pattern that is also observed in real networks (Lind et al., 2007). Here, we study gossip spread in two social network models (Toivonen et al., 2006; Vázquez, 2003) by exploring the parameter space of both models and fitting them to a real Facebook data set. Both models can produce the non-monotonic relationship of real networks more accurately than a standard scale-free model while also exhibiting more realistic variability in gossip spread. Of the two models, the one given in Vázquez (2003) best captures both the expected values and variability of gossip spread.

  16. Online Social Networking and Mental Health

    Science.gov (United States)

    2014-01-01

    Abstract During the past decade, online social networking has caused profound changes in the way people communicate and interact. It is unclear, however, whether some of these changes may affect certain normal aspects of human behavior and cause psychiatric disorders. Several studies have indicated that the prolonged use of social networking sites (SNS), such as Facebook, may be related to signs and symptoms of depression. In addition, some authors have indicated that certain SNS activities might be associated with low self-esteem, especially in children and adolescents. Other studies have presented opposite results in terms of positive impact of social networking on self-esteem. The relationship between SNS use and mental problems to this day remains controversial, and research on this issue is faced with numerous challenges. This concise review focuses on the recent findings regarding the suggested connection between SNS and mental health issues such as depressive symptoms, changes in self-esteem, and Internet addiction. PMID:25192305

  17. Modelling Users` Trust in Online Social Networks

    Directory of Open Access Journals (Sweden)

    Iacob Cătoiu

    2014-02-01

    Full Text Available Previous studies (McKnight, Lankton and Tripp, 2011; Liao, Lui and Chen, 2011 have shown the crucial role of trust when choosing to disclose sensitive information online. This is the case of online social networks users, who must disclose a certain amount of personal data in order to gain access to these online services. Taking into account privacy calculus model and the risk/benefit ratio, we propose a model of users’ trust in online social networks with four variables. We have adapted metrics for the purpose of our study and we have assessed their reliability and validity. We use a Partial Least Squares (PLS based structural equation modelling analysis, which validated all our initial assumptions, indicating that our three predictors (privacy concerns, perceived benefits and perceived risks explain 48% of the variation of users’ trust in online social networks, the resulting variable of our study. We also discuss the implications and further research opportunities of our study.

  18. Online social networking and mental health.

    Science.gov (United States)

    Pantic, Igor

    2014-10-01

    During the past decade, online social networking has caused profound changes in the way people communicate and interact. It is unclear, however, whether some of these changes may affect certain normal aspects of human behavior and cause psychiatric disorders. Several studies have indicated that the prolonged use of social networking sites (SNS), such as Facebook, may be related to signs and symptoms of depression. In addition, some authors have indicated that certain SNS activities might be associated with low self-esteem, especially in children and adolescents. Other studies have presented opposite results in terms of positive impact of social networking on self-esteem. The relationship between SNS use and mental problems to this day remains controversial, and research on this issue is faced with numerous challenges. This concise review focuses on the recent findings regarding the suggested connection between SNS and mental health issues such as depressive symptoms, changes in self-esteem, and Internet addiction.

  19. Customer Intelligence Analytics on Social Networks

    Directory of Open Access Journals (Sweden)

    Brano MARKIĆ

    2016-08-01

    Full Text Available Discovering needs, habits and consumer behavior is the primary task of marketing analytics. It is necessary to integrate marketing and analytical skills with IT skills. Such knowledge integration allows access to data (structured and unstructured, their analysis and finding out information about the opinions, attitudes, needs and behavior of customers. In the paper is set the hypothesis that software tools can collect data (messages from social networks, analyze the content of messages and get to know the attitudes of customers about a product, service, tourist destination with the ultimate goal of improving customer relations. Experimental results are based on the analysis of the content of social network Facebook by using the package and function R language. This language showed a satisfactory application and development power in analysis of textual data on social networks for marketing analytics.

  20. Group colocation behavior in technological social networks.

    Directory of Open Access Journals (Sweden)

    Chloë Brown

    Full Text Available We analyze two large datasets from technological networks with location and social data: user location records from an online location-based social networking service, and anonymized telecommunications data from a European cellphone operator, in order to investigate the differences between individual and group behavior with respect to physical location. We discover agreements between the two datasets: firstly, that individuals are more likely to meet with one friend at a place they have not visited before, but tend to meet at familiar locations when with a larger group. We also find that groups of individuals are more likely to meet at places that their other friends have visited, and that the type of a place strongly affects the propensity for groups to meet there. These differences between group and solo mobility has potential technological applications, for example, in venue recommendation in location-based social networks.

  1. Spatial Epidemic Modelling in Social Networks

    Science.gov (United States)

    Simoes, Joana Margarida

    2005-06-01

    The spread of infectious diseases is highly influenced by the structure of the underlying social network. The target of this study is not the network of acquaintances, but the social mobility network: the daily movement of people between locations, in regions. It was already shown that this kind of network exhibits small world characteristics. The model developed is agent based (ABM) and comprehends a movement model and a infection model. In the movement model, some assumptions are made about its structure and the daily movement is decomposed into four types: neighborhood, intra region, inter region and random. The model is Geographical Information Systems (GIS) based, and uses real data to define its geometry. Because it is a vector model, some optimization techniques were used to increase its efficiency.

  2. The Analysis of Duocentric Social Networks: A Primer.

    Science.gov (United States)

    Kennedy, David P; Jackson, Grace L; Green, Harold D; Bradbury, Thomas N; Karney, Benjamin R

    2015-02-01

    Marriages and other intimate partnerships are facilitated or constrained by the social networks within which they are embedded. To date, methods used to assess the social networks of couples have been limited to global ratings of social network characteristics or network data collected from each partner separately. In the current article, the authors offer new tools for expanding on the existing literature by describing methods of collecting and analyzing duocentric social networks, that is, the combined social networks of couples. They provide an overview of the key considerations for measuring duocentric networks, such as how and why to combine separate network interviews with partners into one shared duocentric network, the number of network members to assess, and the implications of different network operationalizations. They illustrate these considerations with analyses of social network data collected from 57 low-income married couples, presenting visualizations and quantitative measures of network composition and structure.

  3. Social Network Perspective: Model of Student Knowledge Sharing On Social Network Media

    OpenAIRE

    Bentar Priyopradono; Danny Manongga; Wiranto H. Utomo

    2012-01-01

    Recently, the role and development of information technology especially the internet, gives impact and influence in social relationship especially for social network site services users. The impact and influence the use of Internet which is related to exchange information and knowledge sharing still become one of the interesting topics to be researched. Now, the use of social media network by students are the best way to them to increase their knowledge as communication media such as, exchang...

  4. Social network predictors of latrine ownership.

    Science.gov (United States)

    Shakya, Holly B; Christakis, Nicholas A; Fowler, James H

    2015-01-01

    Poor sanitation, including the lack of clean functioning toilets, is a major factor contributing to morbidity and mortality from infectious diseases in the developing world. We examine correlates of latrine ownership in rural India with a focus on social network predictors. Participants from 75 villages provided the names of their social contacts as well as their own relevant demographic and household characteristics. Using these measures, we test whether the latrine ownership of an individual's social contacts is a significant predictor of individual latrine ownership. We also investigate whether network centrality significantly predicts latrine ownership, and if so, whether it moderates the relationship between the latrine ownership of the individual and that of her social contacts. Our results show that, controlling for the standard predictors of latrine ownership such as caste, education, and income, individuals are more likely to own latrines if their social contacts own latrines. Interaction models suggest that this relationship is stronger among those of the same caste, the same education, and those with stronger social ties. We also find that more central individuals are more likely to own latrines, but the correlation in latrine ownership between social contacts is strongest among individuals on the periphery of the network. Although more data is needed to determine how much the clustering of latrine ownership may be caused by social influence, the results here suggest that interventions designed to promote latrine ownership should consider focusing on those at the periphery of the network. The reason is that they are 1) less likely to own latrines and 2) more likely to exhibit the same behavior as their social contacts, possibly as a result of the spread of latrine adoption from one person to another. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Organizational networks and social capital

    DEFF Research Database (Denmark)

    Svendsen, Gunnar Lind Haase; Waldstrøm, Christian

    2013-01-01

    , as well as the derived benefits, or losses. Next, the chapter presents an empirical case apt to illustrate the theoretical findings in part one, namely the nineteenth-century Danish Cooperative Dairy Movement (Svendsen and Svendsen 2004). It is demonstrated how social capital among Danish peasants...

  6. Study on the correlation between the hierarchical urban system and high-speed railway network planning in China

    Directory of Open Access Journals (Sweden)

    Hong Sun

    2016-09-01

    Full Text Available This study examines the interrelatedness between the hierarchical structure of China׳s urban system and high-speed railway (HSR network planning at the national level. As a multi-layered system, the Chinese HSR can be categorized into three sub-networks, namely, the national HSR trunk network, the national HSR extensional network, and the intercity HSR network. By examining the direct HSR network connection, HSR nodal connection, and HSR operational frequency of 287 prefecture-level cities, this study demonstrates that the hierarchies of China׳s administrative, demographic, and economic urban systems strongly influence HSR network planning. The national HSR trunk network prioritizes the connection of top-level central cities, whereas the extensional network prioritizes cities at the lower level of the urban system. Moreover, the national HSR system forms the backbone of the HSR network structure based on a national scale, whereas the intercity HSR system satisfies the travel needs within urban agglomerations based on the regional level.

  7. Social Trust Prediction Using Heterogeneous Networks

    Science.gov (United States)

    HUANG, JIN; NIE, FEIPING; HUANG, HENG; TU, YI-CHENG; LEI, YU

    2014-01-01

    Along with increasing popularity of social websites, online users rely more on the trustworthiness information to make decisions, extract and filter information, and tag and build connections with other users. However, such social network data often suffer from severe data sparsity and are not able to provide users with enough information. Therefore, trust prediction has emerged as an important topic in social network research. Traditional approaches are primarily based on exploring trust graph topology itself. However, research in sociology and our life experience suggest that people who are in the same social circle often exhibit similar behaviors and tastes. To take advantage of the ancillary information for trust prediction, the challenge then becomes what to transfer and how to transfer. In this article, we address this problem by aggregating heterogeneous social networks and propose a novel joint social networks mining (JSNM) method. Our new joint learning model explores the user-group-level similarity between correlated graphs and simultaneously learns the individual graph structure; therefore, the shared structures and patterns from multiple social networks can be utilized to enhance the prediction tasks. As a result, we not only improve the trust prediction in the target graph but also facilitate other information retrieval tasks in the auxiliary graphs. To optimize the proposed objective function, we use the alternative technique to break down the objective function into several manageable subproblems. We further introduce the auxiliary function to solve the optimization problems with rigorously proved convergence. The extensive experiments have been conducted on both synthetic and real- world data. All empirical results demonstrate the effectiveness of our method. PMID:24729776

  8. Mapping social networks in software process improvement

    DEFF Research Database (Denmark)

    Tjørnehøj, Gitte; Nielsen, Peter Axel

    2005-01-01

    Software process improvement in small, agile organizations is often problematic. Model-based approaches seem to overlook problems. We have been seeking an alternative approach to overcome this through action research. Here we report on a piece of action research from which we developed an approach...... to map social networks and suggest how it can be used in software process improvement. We applied the mapping approach in a small software company to support the realization of new ways of improving software processes. The mapping approach was found useful in improving social networks, and thus furthers...... software process improvement....

  9. Analysis of Privacy on Social Networks

    OpenAIRE

    Tomandl, Luboš

    2015-01-01

    This thesis deals with a question of privacy in a context of social networks. The main substance of these services is the users' option to share an information about their lives. This alone can be a problem for privacy. In the first part of this thesis concentrates on the meaning of privacy as well as its value for both individuals and the society. In the next part the privacy threats on social networks, namely Facebook, are discussed. These threats are disclosed on four levels according to f...

  10. Summary how Google's social network changes everything

    CERN Document Server

    2014-01-01

    This work offers a summary of the book: « Google+ for business: How Google's Social Network Changes Everything » by Chris Brogan.Summary of the ideas in Chris Brogan's book « Google+ for business » highlights that the social network created by Google now has lore than 175 million users and is tied to the largest search engines in the world. Therefore, Google+ could end up being the best online business building tool ever developed. So if you can master using Google+ today, you will be well positioned for what happens in the future as Google, YouTube and others continue to bring new developmen

  11. Tourist destination branding on social networks

    Directory of Open Access Journals (Sweden)

    Radenković-Šošić Bojana

    2012-06-01

    Full Text Available Social networks have become the modern means of communication. Intensive electronic word of mouth to mouth (eWOM leads to faster sharing of experiences, and the creation of positive and negative attitudes. On the other hand, branding of tourist destinations has become one of the most powerful resources in the implementation of marketing strategies in tourism. The aim of this study, which is based on primary research, is to examine the concept of electronic word of mouth, as well as the role of social networks in the process of branding tourist destinations.

  12. On Hierarchical Extensions of Large-Scale 4-regular Grid Network Structures

    DEFF Research Database (Denmark)

    Pedersen, Jens Myrup; Patel, A.; Knudsen, Thomas Phillip

    2004-01-01

    dependencies between the number of nodes and the distances in the structures. The perfect square mesh is introduced for hierarchies, and it is shown that applying ordered hierarchies in this way results in logarithmic dependencies between the number of nodes and the distances, resulting in better scaling...... structures. For example, in a mesh of 391876 nodes the average distance is reduced from 417.33 to 17.32 by adding hierarchical lines. This is gained by increasing the number of lines by 4.20% compared to the non-hierarchical structure. A similar hierarchical extension of the torus structure also results...

  13. Social networks and cooperation: a bibliometric study

    Directory of Open Access Journals (Sweden)

    Ana Paula Lopes

    2013-05-01

    Full Text Available The social network analysis involves social and behavioral science. The decentralization of productive activities, such as the formation of "network organizations" as a result of downsizing of large corporate structures of the past, marked by outsoucing and formation of alliances, shows the importance of this theme. The main objective of this paper is to analyze the theory of cooperation and social networks over a period of 24 years. For this, was performed a bibliometric study with content analysis. The database chosen for the initial sample search was ISI Web of Science. The search topics were “social network” and “cooperation”. Were analyzed 97 articles and their references, through networks of citations. The main identified research groups dealing with issues related to trust, strategic alliances, natural cooperation, game theory, social capital, intensity of interaction, reciprocity and innovation. It was found that the publications occurred in a large number of journals, which indicates that the theme is multidisciplinary, and only five journals published at least three articles. Although the first publication has occurred in 1987, was from 2006 that the publications effectively increased. The areas most related to the theme of the research were performance, evolution, management, graphics, model and game theory.

  14. Social inertia and diversity in collaboration networks

    Science.gov (United States)

    Ramasco, J. J.

    2007-04-01

    Random graphs are useful tools to study social interactions. In particular, the use of weighted random graphs allows to handle a high level of information concerning which agents interact and in which degree the interactions take place. Taking advantage of this representation, we recently defined a magnitude, the Social Inertia, that measures the eagerness of agents to keep ties with previous partners. To study this magnitude, we used collaboration networks that are specially appropriate to obtain valid statitical results due to the large size of publically available databases. In this work, I study the Social Inertia in two of these empirical networks, IMDB movie database and condmat. More specifically, I focus on how the Inertia relates to other properties of the graphs, and show that the Inertia provides information on how the weight of neighboring edges correlates. A social interpretation of this effect is also offered.

  15. Social contagion theory: examining dynamic social networks and human behavior

    OpenAIRE

    Christakis, Nicholas A.; Fowler, James H.

    2012-01-01

    Here, we review the research we have done on social contagion. We describe the methods we have employed (and the assumptions they have entailed) in order to examine several datasets with complementary strengths and weaknesses, including the Framingham Heart Study, the National Longitudinal Study of Adolescent Health, and other observational and experimental datasets that we and others have collected. We describe the regularities that led us to propose that human social networks may exhibit a ...

  16. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.

    Science.gov (United States)

    Herrera, Mauricio; Armelini, Guillermo; Salvaj, Erica

    2015-01-01

    There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions.

  17. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.

    Directory of Open Access Journals (Sweden)

    Mauricio Herrera

    Full Text Available There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions.

  18. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks

    Science.gov (United States)

    2015-01-01

    There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions. PMID:26505473

  19. Fractal Analysis of Mobile Social Networks

    International Nuclear Information System (INIS)

    Zheng Wei; Pan Qian; Sun Chen; Deng Yu-Fan; Zhao Xiao-Kang; Kang Zhao

    2016-01-01

    Fractal and self similarity of complex networks have attracted much attention in recent years. The fractal dimension is a useful method to describe the fractal property of networks. However, the fractal features of mobile social networks (MSNs) are inadequately investigated. In this work, a box-covering method based on the ratio of excluded mass to closeness centrality is presented to investigate the fractal feature of MSNs. Using this method, we find that some MSNs are fractal at different time intervals. Our simulation results indicate that the proposed method is available for analyzing the fractal property of MSNs. (paper)

  20. Social Networks, Ethnicity, and Entrepreneurship

    OpenAIRE

    Kerr, William R.; Mandorff, Martin

    2016-01-01

    We study the relationship between ethnicity, occupational choice, and entrepreneurship. Immigrant groups in the United States cluster in specific business sectors. For example, the concentration of Korean self-employment in dry cleaners is 34 times greater than other immigrant groups, and Gujarati-speaking Indians are similarly 108 times more concentrated in managing motels. We develop a model of social interactions where non-work relationships facilitate the acquisition of sector-specific sk...

  1. When business networks “kill” social networks

    DEFF Research Database (Denmark)

    Jackson, Laurel; Young, L.

    2016-01-01

    that considers the changes to a community's social network and the associated norms emerging from the growing influence of a microfinance providers' network. A case study reports the impact of microfinance on a particular Bangladesh rural community. We show there is a breakdown in traditional social networks...... in this and other poor rural villages brought about by the taking of micro loans when the families have no means of paying them back. This increased indebtedness to NGOs is perpetuating their poverty and diminishing the community's quality of life including their traditions of bounded solidarity, where families...... in the economic structure of rural Bangladesh and changing norms, in particular the changes to traditional forms of financial exchange and associated support and risk management. We conclude that public policy and a different business model that is more accountable and altruistic are needed to guide...

  2. Evolution of a large online social network

    International Nuclear Information System (INIS)

    Hu Haibo; Wang Xiaofan

    2009-01-01

    Although recently there are extensive research on the collaborative networks and online communities, there is very limited knowledge about the actual evolution of the online social networks (OSN). In the Letter, we study the structural evolution of a large online virtual community. We find that the scale growth of the OSN shows non-trivial S shape which may provide a proper exemplification for Bass diffusion model. We reveal that the evolutions of many network properties, such as density, clustering, heterogeneity and modularity, show non-monotone feature, and shrink phenomenon occurs for the path length and diameter of the network. Furthermore, the OSN underwent a transition from degree assortativity characteristic of collaborative networks to degree disassortativity characteristic of many OSNs. Our study has revealed the evolutionary pattern of interpersonal interactions in a specific population and provided a valuable platform for theoretical modeling and further analysis

  3. Online social network data as sociometric markers.

    Science.gov (United States)

    Binder, Jens F; Buglass, Sarah L; Betts, Lucy R; Underwood, Jean D M

    2017-10-01

    Data from online social networks carry enormous potential for psychological research, yet their use and the ethical implications thereof are currently hotly debated. The present work aims to outline in detail the unique information richness of this data type and, in doing so, to support researchers when deciding on ethically appropriate ways of collecting, storing, publishing, and sharing data from online sources. Focusing on the very nature of social networks, their structural characteristics, and depth of information, we provide a detailed and accessible account of the challenges associated with data management and data storage. In particular, the general nonanonymity of network data sets is discussed, and an approach is developed to quantify the level of uniqueness that a particular online network bestows upon the individual maintaining it. Using graph enumeration techniques, we show that comparatively sparse information on a network is suitable as a sociometric marker that allows for the identification of an individual from the global population of online users. The impossibility of anonymizing specific types of network data carries implications for ethical guidelines and research practice. At the same time, network uniqueness opens up opportunities for novel research in psychology. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  4. Vertical Transmission of Social Roles Drives Resilience to Poaching in Elephant Networks.

    Science.gov (United States)

    Goldenberg, Shifra Z; Douglas-Hamilton, Iain; Wittemyer, George

    2016-01-11

    Network resilience to perturbation is fundamental to functionality in systems ranging from synthetic communication networks to evolved social organization [1]. While theoretical work offers insight into causes of network robustness, examination of natural networks can identify evolved mechanisms of resilience and how they are related to the selective pressures driving structure. Female African elephants (Loxodonta africana) exhibit complex social networks with node heterogeneity in which older individuals serve as connectivity hubs [2, 3]. Recent ivory poaching targeting older elephants in a well-studied population has mirrored the targeted removal of highly connected nodes in the theoretical literature that leads to structural collapse [4, 5]. Here we tested the response of this natural network to selective knockouts. We find that the hierarchical network topology characteristic of elephant societies was highly conserved across the 16-year study despite ∼70% turnover in individual composition of the population. At a population level, the oldest available individuals persisted to fill socially central positions in the network. For analyses using known mother-daughter pairs, social positions of daughters during the disrupted period were predicted by those of their mothers in years prior, were unrelated to individual histories of family mortality, and were actively built. As such, daughters replicated the social network roles of their mothers, driving the observed network resilience. Our study provides a rare bridge between network theory and an evolved system, demonstrating social redundancy to be the mechanism by which resilience to perturbation occurred in this socially advanced species. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Discrete Opinion Dynamics on Online Social Networks

    Science.gov (United States)

    Hu, Yan-Li; Bai, Liang; Zhang, Wei-Ming

    2013-01-01

    This paper focuses on the dynamics of binary opinions {+1, -1} on online social networks consisting of heterogeneous actors. In our model, actors update their opinions under the interplay of social influence and self- affirmation, which leads to rich dynamical behaviors on online social networks. We find that the opinion leading to the consensus features an advantage of the initially weighted fraction based on actors' strength over the other, instead of the population. For the role of specific actors, the consensus converges towards the opinion that a small fraction of high-strength actors hold, and individual diversity of self-affirmation slows down the ordering process of consensus. These indicate that high-strength actors play an essential role in opinion formation with strong social influence as well as high persistence. Further investigations show that the initial fraction of high-strength actors to dominate the evolution depends on the heterogeneity of the strength distribution, and less high-strength actors are needed in the case of a smaller exponent of power-law distribution of actors' strength. Our study provides deep insights into the role of social influence and self-affirmation on opinion formation on online social networks.

  6. Discrete Opinion Dynamics on Online Social Networks

    International Nuclear Information System (INIS)

    Hu Yan-Li; Bai Liang; Zhang Wei-Ming

    2013-01-01

    This paper focuses on the dynamics of binary opinions {+1, −1} on online social networks consisting of heterogeneous actors. In our model, actors update their opinions under the interplay of social influence and self- affirmation, which leads to rich dynamical behaviors on online social networks. We find that the opinion leading to the consensus features an advantage of the initially weighted fraction based on actors' strength over the other, instead of the population. For the role of specific actors, the consensus converges towards the opinion that a small fraction of high-strength actors hold, and individual diversity of self-affirmation slows down the ordering process of consensus. These indicate that high-strength actors play an essential role in opinion formation with strong social influence as well as high persistence. Further investigations show that the initial fraction of high-strength actors to dominate the evolution depends on the heterogeneity of the strength distribution, and less high-strength actors are needed in the case of a smaller exponent of power-law distribution of actors' strength. Our study provides deep insights into the role of social influence and self-affirmation on opinion formation on online social networks. (general)

  7. Interference mitigation for broadcast in hierarchical cell structure networks: Transmission strategy and area spectral efficiency

    KAUST Repository

    Yang, Yuli; Salama, Khaled N.; Aï ssa, Sonia

    2014-01-01

    In this paper, a hierarchical cell structure (HCS) is considered, where an access point (AP) broadcasts to local nodes (LNs) over orthogonal frequency subbands within a local cell located in a macrocell. Since the local cell shares the spectrum

  8. The association between social network factors and mental health at different life stages.

    Science.gov (United States)

    Levula, Andrew; Wilson, Andrew; Harré, Michael

    2016-07-01

    Psychosocial factors are important determinants of an individual's health. This study examines the association between health scores and social network factors on mental health across different life stages. Data were drawn from the Household Income and Labour Dynamics in Australia survey for adolescents (n = 1739), adults (n = 10,309) and seniors (n = 2287). Hierarchical regression modelling was applied to examine effects within and across age groups. All the variables were derived from the self-completion questionnaire. The social network factors were statistically significant predictors of mental health outcomes for all three life stages. For adolescents, the three social network factors were statistically significant with social isolation having the largest impact (β = -.284, p social connection (β = .084, p social trust having a similar effect (β = .073, p social isolation had the highest impact (β = -.203, p social connection (β = .110, p social trust (β = .087, p social isolation (β = -.188, p social connection (β = .147, p social trust (β = .032, p social network factors, the models improved significantly with social isolation playing the most significant role across all life stages, whereas the other social network factors played a differentiated role depending upon the life stage. These findings have practical implications in the design of mental health interventions across different life stages.

  9. Consuming Social Networks: A Study on BeeTalk Network

    Directory of Open Access Journals (Sweden)

    Jamal Mohammadi

    Full Text Available BeeTalk is one of the most common social networks that have attracted many users during these years. As a whole, social networks are parts of everyday life nowadays and, especially among the new generation, have caused some basic alterations in the field of identity-formation, sense-making and the form and content of communication. This article is a research about BeeTalk users, their virtual interactions and experiences, and the feelings, pleasures, meanings and attitudes that they obtain through participating in the virtual world. This is a qualitative research. The sample is selected by way of theoretical sampling among the students of University of Kurdistan. Direct observation and semistructured interviews are used to gathering data, which are interpreted through grounded theory. The findings show that some contexts like “searching real interests in a non-real world” and “the representation of users’ voices in virtual space” have provided the space for participating in BeeTalk, and an intervening factor called “instant availability” has intensified this participation. Users’ participation in this social network has changed their social interaction in the real world and formed some new types of communication among them such as “representation of faked identities”, “experiencing ceremonial space” and “artificial literacy”. Moreover, this participation has some consequences like “virtual addiction” and “virtual collectivism” in users’ everyday life that effects their ways of providing meaning and identity in their social lives. It can be said that the result of user’s activity in this network is to begin a kind of simulated relation that has basic differences with relations in the real world. The experience of relation in this network lacks nobility, enrichment and animation, rather it is instant, artificial and without any potential to vitalization.

  10. The fluency of social hierarchy: the ease with which hierarchical relationships are seen, remembered, learned, and liked.

    Science.gov (United States)

    Zitek, Emily M; Tiedens, Larissa Z

    2012-01-01

    We tested the hypothesis that social hierarchies are fluent social stimuli; that is, they are processed more easily and therefore liked better than less hierarchical stimuli. In Study 1, pairs of people in a hierarchy based on facial dominance were identified faster than pairs of people equal in their facial dominance. In Study 2, a diagram representing hierarchy was memorized more quickly than a diagram representing equality or a comparison diagram. This faster processing led the hierarchy diagram to be liked more than the equality diagram. In Study 3, participants were best able to learn a set of relationships that represented hierarchy (asymmetry of power)--compared to relationships in which there was asymmetry of friendliness, or compared to relationships in which there was symmetry--and this processing ease led them to like the hierarchy the most. In Study 4, participants found it easier to make decisions about a company that was more hierarchical and thus thought the hierarchical organization had more positive qualities. In Study 5, familiarity as a basis for the fluency of hierarchy was demonstrated by showing greater fluency for male than female hierarchies. This study also showed that when social relationships are difficult to learn, people's preference for hierarchy increases. Taken together, these results suggest one reason people might like hierarchies--hierarchies are easy to process. This fluency for social hierarchies might contribute to the construction and maintenance of hierarchies.

  11. Review of Social Networking Sites' Security and Privacy

    OpenAIRE

    YANG, SHUN

    2015-01-01

    Nowadays social media networking has dramatically increased. Social networking sites like Facebook make users create huge amount of profiles and share personal information within networking of different users. Social networking exposes personal information far beyond the group of friends. And that information or data on social media networking could be potential threat to people's information security and privacy. In this review, we are going to view the privacy risks and security problem...

  12. The Application of Social Network Analysis to Team Sports

    Science.gov (United States)

    Lusher, Dean; Robins, Garry; Kremer, Peter

    2010-01-01

    This article reviews how current social network analysis might be used to investigate individual and group behavior in sporting teams. Social network analysis methods permit researchers to explore social relations between team members and their individual-level qualities simultaneously. As such, social network analysis can be seen as augmenting…

  13. Predicting the evolution of social networks with life cycle events

    NARCIS (Netherlands)

    Sharmeen, F.; Arentze, T.A.; Timmermans, H.J.P.

    2015-01-01

    This paper presents a model of social network evolution, to predict and simulate changes in social networks induced by lifecycle events. We argue that social networks change with lifecycle events, and we extend a model of friendship selection to incorporate these dynamics of personal social

  14. Social Network Methods for the Educational and Psychological Sciences

    Science.gov (United States)

    Sweet, Tracy M.

    2016-01-01

    Social networks are especially applicable in educational and psychological studies involving social interactions. A social network is defined as a specific relationship among a group of individuals. Social networks arise in a variety of situations such as friendships among children, collaboration and advice seeking among teachers, and coauthorship…

  15. Composite Social Network for Predicting Mobile Apps Installation

    Science.gov (United States)

    2011-06-02

    Social network tools (such as the Facebook app and the Twitter app) can observe users’ online friendship network . In this work, our key idea is...the friendship network from phones by collecting data from social networking apps such as the Facebook and Twitter apps. We summarize all the networks ...ar X iv :1 10 6. 03 59 v1 [ cs .S I] 2 J un 2 01 1 Composite Social Network for Predicting Mobile Apps Installation Wei Pan

  16. Online social network sites and social capital: a case of facebook

    OpenAIRE

    Naseri, Samaneh

    2017-01-01

    The present study is a theoretical and literary review of online social network sites and their impact on social capital. In this review, the Facebook is selected as one popular and important online social networking site in the world today. To This end, first two main concepts of social capital, bridging and bonding social capital has been provided. Next, the concept of online social networks and the impact of FB on social networks are discussed.

  17. Social networks and mental health among a farming population.

    Science.gov (United States)

    Stain, Helen J; Kelly, Brian; Lewin, Terry J; Higginbotham, Nick; Beard, John R; Hourihan, Fleur

    2008-10-01

    The study investigated the associations between mental health and measures of community support, social support networks, sense of place, adversity, and perceived problems in a rural Australian population. There was a specific focus on farming communities due to previous qualitative research by the authors indicating distress by farmers in response to drought (Sartore et al. Aust Fam Phys 36(12), 990-993, 2007). A survey was mailed to adults randomly selected from the Australian Electoral Roll and residing within four local government areas (LGAs) of varying remoteness in rural New South Wales (NSW). Survey measures included: support networks and community attachment; recent stressors (including drought-related stress); and measures of health and related functioning. The Kessler-10 provided an index of current psychological distress. The sample (n = 449; response rate 24%) was predominantly female (58.4%) and 18.9% were farmers or farm workers. Moderate to very high psychological distress was reported for 20.7% of the sample. Half (56.1%) of all respondents, and specifically 71.8% of farmers or farm workers, reported high levels of perceived stress due to drought. Psychological distress was associated with recent adverse life events, increased alcohol use and functional impairment. Hierarchical regression analysis demonstrated an independent effect of the number of stressful life events including drought related stress, perceived social support (community and individual), alcohol use and physical functioning ability on levels of psychological distress. This model accounted for 43% of the variance in current levels of distress. Lower community support had a more marked impact on distress levels for non-farming than farming participants. This study has highlighted the association between unique rural community characteristics and rural stressors (such as drought) and measures of mental health, suggesting the important mediating role of social factors and community

  18. Social networking sites and older users - a systematic review

    OpenAIRE

    Nef, Tobias; Ganea, Raluca L.; Müri, René M.; Mosimann, Urs P.

    2017-01-01

    BACKGROUND Social networking sites can be beneficial for senior citizens to promote social participation and to enhance intergenerational communication. Particularly for older adults with impaired mobility, social networking sites can help them to connect with family members and other active social networking users. The aim of this systematic review is to give an overview of existing scientific literature on social networking in older users. METHODS Computerized databases were sea...

  19. Discovering Social Circles in Ego Networks (Author’s Manuscript)

    Science.gov (United States)

    2013-01-10

    refer to as social cir- cles. Practically all major social networks provide such functionality, for example, ‘circles’ on Google+, and ‘lists’ on Facebook ...Discovering Social Circles in Ego Networks Julian McAuley and Jure Leskovec Stanford jmcauley@cs.stanford.edu, jure@cs.stanford.edu January 11, 2013...Abstract People’s personal social networks are big and cluttered, and currently there is no good way to automatically organize them. Social networking

  20. THE IMPACTS OF SOCIAL NETWORKING SITES IN HIGHER LEARNING

    OpenAIRE

    Mohd Ishak Bin Ismail; Ruzaini Bin Abdullah Arshah

    2016-01-01

    Social networking sites, a web-based application have permeated the boundary between personal lives and student lives. Nowadays, students in higher learning used social networking site such as Facebook to facilitate their learning through the academic collaboration which it further enhances students’ social capital. Social networking site has many advantages to improve students’ learning. To date, Facebook is the leading social networking sites at this time which it being widely used by stude...