WorldWideScience

Sample records for complex social networks

  1. Social networks as embedded complex adaptive systems.

    Science.gov (United States)

    Benham-Hutchins, Marge; Clancy, Thomas R

    2010-09-01

    As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 15th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, the authors discuss healthcare social networks as a hierarchy of embedded complex adaptive systems. The authors further examine the use of social network analysis tools as a means to understand complex communication patterns and reduce medical errors.

  2. Disease Surveillance on Complex Social Networks.

    Directory of Open Access Journals (Sweden)

    Jose L Herrera

    2016-07-01

    Full Text Available As infectious disease surveillance systems expand to include digital, crowd-sourced, and social network data, public health agencies are gaining unprecedented access to high-resolution data and have an opportunity to selectively monitor informative individuals. Contact networks, which are the webs of interaction through which diseases spread, determine whether and when individuals become infected, and thus who might serve as early and accurate surveillance sensors. Here, we evaluate three strategies for selecting sensors-sampling the most connected, random, and friends of random individuals-in three complex social networks-a simple scale-free network, an empirical Venezuelan college student network, and an empirical Montreal wireless hotspot usage network. Across five different surveillance goals-early and accurate detection of epidemic emergence and peak, and general situational awareness-we find that the optimal choice of sensors depends on the public health goal, the underlying network and the reproduction number of the disease (R0. For diseases with a low R0, the most connected individuals provide the earliest and most accurate information about both the onset and peak of an outbreak. However, identifying network hubs is often impractical, and they can be misleading if monitored for general situational awareness, if the underlying network has significant community structure, or if R0 is high or unknown. Taking a theoretical approach, we also derive the optimal surveillance system for early outbreak detection but find that real-world identification of such sensors would be nearly impossible. By contrast, the friends-of-random strategy offers a more practical and robust alternative. It can be readily implemented without prior knowledge of the network, and by identifying sensors with higher than average, but not the highest, epidemiological risk, it provides reasonably early and accurate information.

  3. Identifying Social Communities in Complex Communications for Network Efficiency

    Science.gov (United States)

    Hui, Pan; Yoneki, Eiko; Crowcroft, Jon; Chan, Shu-Yan

    Complex communication networks, more particular Mobile Ad Hoc Networks (MANET) and Pocket Switched Networks (PSN), rely on short range radio and device mobility to transfer data across the network. These kind of mobile networks contain duality in nature: they are radio networks at the same time also human networks, and hence knowledge from social networks can be also applicable here. In this paper, we demonstrate how identifying social communities can significantly improve the forwarding efficiencies in term of delivery ratio and delivery cost. We verify our hypothesis using data from five human mobility experiments and test on two application scenarios, asynchronous messaging and publish/subscribe service.

  4. Centrality Robustness and Link Prediction in Complex Social Networks

    DEFF Research Database (Denmark)

    Davidsen, Søren Atmakuri; Ortiz-Arroyo, Daniel

    2012-01-01

    This chapter addresses two important issues in social network analysis that involve uncertainty. Firstly, we present am analysis on the robustness of centrality measures that extend the work presented in Borgati et al. using three types of complex network structures and one real social network....... Secondly, we present a method to predict edges in dynamic social networks. Our experimental results indicate that the robustness of the centrality measures applied to more realistic social networks follows a predictable pattern and that the use of temporal statistics could improve the accuracy achieved...

  5. Hierarchical community structure in complex (social) networks

    CERN Document Server

    Massaro, Emanuele

    2014-01-01

    The investigation of community structure in networks is a task of great importance in many disciplines, namely physics, sociology, biology and computer science where systems are often represented as graphs. One of the challenges is to find local communities from a local viewpoint in a graph without global information in order to reproduce the subjective hierarchical vision for each vertex. In this paper we present the improvement of an information dynamics algorithm in which the label propagation of nodes is based on the Markovian flow of information in the network under cognitive-inspired constraints \\cite{Massaro2012}. In this framework we have introduced two more complex heuristics that allow the algorithm to detect the multi-resolution hierarchical community structure of networks from a source vertex or communities adopting fixed values of model's parameters. Experimental results show that the proposed methods are efficient and well-behaved in both real-world and synthetic networks.

  6. The complexity of older adults' social support networks.

    Science.gov (United States)

    Chaichanawirote, Uraiwan; Higgins, Patricia A

    2013-10-01

    The purpose of this study was to provide a detailed snapshot of the diversity of social support networks of 95 independent-living older adults (mean age = 76). Participants in the convenience sample were recruited from senior centers and a retirement community. Using the Arizona Social Support Interview Schedule and egocentric network analysis, participants' networks are described in terms of patterns, density, size of positive networks (available and utilized), size of negative networks (available and utilized), support need, and support satisfaction. Each participant and the identified members of his or her network were considered a complex adaptive system. Network boundary was 7 members; average network size was 6.22 members (SD = 1.50); network density was moderate (mean = 0.53, SD = 0.33); positive interaction networks were larger than negative networks; and overall, participants reported moderate support need (mean = 2.5, SD = 0.7) and high support satisfaction (mean = 5.9, SD = 1.0).

  7. Critical phenomena of social complex network

    CERN Document Server

    Genzor, Jozef; Gendiar, Andrej

    2014-01-01

    We propose a multi-state spin model in order to describe equilibrial behavior of a society. Our physical spin system is inspired by the Axelrod model used in social network studies. In the framework of the statistical mechanics language, we analyze phase transitions of our model in which the spin interactions are interpreted as a mutual communication among individuals forming a society. The thermal fluctuations introduce a noise into the communication which suppresses long-range correlations. Below a certain phase transition point, large-scale groups of the individuals, who share a specific dominant property, are formed. The measure of the group sizes is an order parameter after the spontaneous symmetry breaking mechanism has occurred. By means of the Corner transfer matrix renormalization group algorithm, we treat our model in the thermodynamic limit and classify the phase transitions with respect to inherent degrees of freedom. Each individual is chosen to have two independent features and each feature has ...

  8. Complexity and state-transitions in social dependence networks

    Directory of Open Access Journals (Sweden)

    Giuliano Pistolesi

    2001-01-01

    Full Text Available Computation of complexity in Social Dependence Networks is an interesting research domain to understand evolution processes and group exchange dynamics in natural and artificial intelligent Multi-Agent Systems. We perform an agent-based simulation by NET-PLEX (Conte and Pistolesi, 2000, a new software system able both to build interdependence networks tipically emerging in Multi-Agent System scenarios and to investigate complexity phenomena, i.e., unstability and state-transitions like Hopf bifurcation (Nowak and Lewenstein, 1994, and to describe social self organization phenomena emerging in these artificial social systems by means of complexity measures similar to those introduced by Hubermann and Hogg (1986. By performing analysis of complexity in these kind of artificial societies we observed interesting phenomena in emerging organizations that suggest state-transitions induced by critical configurations of parameters describing the social system similar to those observed in many studies on state-transitions in bifurcation chaos (Schuster, 1988; Ruelle, 1989.

  9. Bidirectional selection between two classes in complex social networks

    CERN Document Server

    Zhou, Bin; Jiang, Luo-Luo; Wang, Nian-Xin; Wang, Bing-Hong

    2015-01-01

    The bidirectional selection between two classes widely emerges in various social lives, such as commercial trading and mate choosing. Until now, the discussions on bidirectional selection in structured human society are quite limited. We demonstrated theoretically that the rate of successfully matching is affected greatly by individuals neighborhoods in social networks, regardless of the type of networks. Furthermore, it is found that the high average degree of networks contributes to increasing rates of successful matches. The matching performance in different types of networks has been quantitatively investigated, revealing that the small-world networks reinforces the matching rate more than scale-free networks at given average degree. In addition, our analysis is consistent with the modeling result, which provides the theoretical understanding of underlying mechanisms of matching in complex networks.

  10. Complex social contagion makes networks more vulnerable to disease outbreaks

    CERN Document Server

    Campbell, Ellsworth

    2012-01-01

    Social network analysis is now widely used to investigate the dynamics of infectious disease spread from person to person. Vaccination dramatically disrupts the disease transmission process on a contact network, and indeed, sufficiently high vaccination rates can disrupt the process to such an extent that disease transmission on the network is effectively halted. Here, we build on mounting evidence that health behaviors - such as vaccination, and refusal thereof - can spread through social networks through a process of complex contagion that requires social reinforcement. Using network simulations that model both the health behavior and the infectious disease spread, we find that under otherwise identical conditions, the process by which the health behavior spreads has a very strong effect on disease outbreak dynamics. This variability in dynamics results from differences in the topology within susceptible communities that arise during the health behavior spreading process, which in turn depends on the topolo...

  11. Evolution of Cooperation in Social Dilemmas on Complex Networks.

    Science.gov (United States)

    Iyer, Swami; Killingback, Timothy

    2016-02-01

    Cooperation in social dilemmas is essential for the functioning of systems at multiple levels of complexity, from the simplest biological organisms to the most sophisticated human societies. Cooperation, although widespread, is fundamentally challenging to explain evolutionarily, since natural selection typically favors selfish behavior which is not socially optimal. Here we study the evolution of cooperation in three exemplars of key social dilemmas, representing the prisoner's dilemma, hawk-dove and coordination classes of games, in structured populations defined by complex networks. Using individual-based simulations of the games on model and empirical networks, we give a detailed comparative study of the effects of the structural properties of a network, such as its average degree, variance in degree distribution, clustering coefficient, and assortativity coefficient, on the promotion of cooperative behavior in all three classes of games.

  12. Evolution of Cooperation in Social Dilemmas on Complex Networks.

    Directory of Open Access Journals (Sweden)

    Swami Iyer

    2016-02-01

    Full Text Available Cooperation in social dilemmas is essential for the functioning of systems at multiple levels of complexity, from the simplest biological organisms to the most sophisticated human societies. Cooperation, although widespread, is fundamentally challenging to explain evolutionarily, since natural selection typically favors selfish behavior which is not socially optimal. Here we study the evolution of cooperation in three exemplars of key social dilemmas, representing the prisoner's dilemma, hawk-dove and coordination classes of games, in structured populations defined by complex networks. Using individual-based simulations of the games on model and empirical networks, we give a detailed comparative study of the effects of the structural properties of a network, such as its average degree, variance in degree distribution, clustering coefficient, and assortativity coefficient, on the promotion of cooperative behavior in all three classes of games.

  13. Rumor spreading model with noise interference in complex social networks

    Science.gov (United States)

    Zhu, Liang; Wang, Youguo

    2017-03-01

    In this paper, a modified susceptible-infected-removed (SIR) model has been proposed to explore rumor diffusion on complex social networks. We take variation of connectivity into consideration and assume the variation as noise. On the basis of related literature on virus networks, the noise is described as standard Brownian motion while stochastic differential equations (SDE) have been derived to characterize dynamics of rumor diffusion both on homogeneous networks and heterogeneous networks. Then, theoretical analysis on homogeneous networks has been demonstrated to investigate the solution of SDE model and the steady state of rumor diffusion. Simulations both on Barabási-Albert (BA) network and Watts-Strogatz (WS) network display that the addition of noise accelerates rumor diffusion and expands diffusion size, meanwhile, the spreading speed on BA network is much faster than on WS network under the same noise intensity. In addition, there exists a rumor diffusion threshold in statistical average meaning on homogeneous network which is absent on heterogeneous network. Finally, we find a positive correlation between peak value of infected individuals and noise intensity while a negative correlation between rumor lifecycle and noise intensity overall.

  14. Social-network complexity in humans is associated with the neural response to social information.

    Science.gov (United States)

    Dziura, Sarah L; Thompson, James C

    2014-11-01

    Humans have evolved to thrive in large and complex social groups, and it is likely that this increase in group complexity has come with a greater need to decode and respond to complex and uncertain communicatory signals. In this functional MRI study, we examined whether complexity of social networks in humans is related to the functioning of brain regions key to the perception of basic, nonverbal social stimuli. Greater activation to biological than to scrambled motion in the right posterior superior temporal sulcus (pSTS) and right amygdala were positively correlated with the diversity of social-network roles. In the pSTS, in particular, this association was not due to a relationship between network diversity and network size. These findings suggest that increased functioning of brain regions involved in decoding social signals might facilitate the detection and decoding of subtle signals encountered in varied social settings.

  15. A System for Social Network Extraction of Web Complex Structures

    OpenAIRE

    Amir Ansari; Mehrdad Jalali

    2011-01-01

    A social network is social structure composed of nodes which generally are individually or organizationally and are connected based on several common traits. Currently, social networks are applied in wide parts of the web. Its popularity is due to discovery of connections hidden in the web and its representation in a visual manner. Social networks are used in many levels from households to nations. They play an important role in finding solutions to problems, management of organizations and i...

  16. Research on Critical Nodes Algorithm in Social Complex Networks

    Science.gov (United States)

    Wang, Xue-Guang

    2017-01-01

    Discovering critical nodes in social networks has many important applications and has attracted more and more institutions and scholars. How to determine the K critical nodes with the most influence in a social network is a NP (define) problem. Considering the widespread community structure, this paper presents an algorithm for discovering critical nodes based on two information diffusion models and obtains each node's marginal contribution by using a Monte-Carlo method in social networks. The solution of the critical nodes problem is the K nodes with the highest marginal contributions. The feasibility and effectiveness of our method have been verified on two synthetic datasets and four real datasets.

  17. Impact of Social Punishment on Cooperative Behavior in Complex Networks

    Science.gov (United States)

    Wang, Zhen; Xia, Cheng-Yi; Meloni, Sandro; Zhou, Chang-Song; Moreno, Yamir

    2013-10-01

    Social punishment is a mechanism by which cooperative individuals spend part of their resources to penalize defectors. In this paper, we study the evolution of cooperation in 2-person evolutionary games on networks when a mechanism for social punishment is introduced. Specifically, we introduce a new kind of role, punisher, which is aimed at reducing the earnings of defectors by applying to them a social fee. Results from numerical simulations show that different equilibria allowing the three strategies to coexist are possible as well as that social punishment further enhance the robustness of cooperation. Our results are confirmed for different network topologies and two evolutionary games. In addition, we analyze the microscopic mechanisms that give rise to the observed macroscopic behaviors in both homogeneous and heterogeneous networks. Our conclusions might provide additional insights for understanding the roots of cooperation in social systems.

  18. Coevolving complex networks in the model of social interactions

    Science.gov (United States)

    Raducha, Tomasz; Gubiec, Tomasz

    2017-04-01

    We analyze Axelrod's model of social interactions on coevolving complex networks. We introduce four extensions with different mechanisms of edge rewiring. The models are intended to catch two kinds of interactions-preferential attachment, which can be observed in scientists or actors collaborations, and local rewiring, which can be observed in friendship formation in everyday relations. Numerical simulations show that proposed dynamics can lead to the power-law distribution of nodes' degree and high value of the clustering coefficient, while still retaining the small-world effect in three models. All models are characterized by two phase transitions of a different nature. In case of local rewiring we obtain order-disorder discontinuous phase transition even in the thermodynamic limit, while in case of long-distance switching discontinuity disappears in the thermodynamic limit, leaving one continuous phase transition. In addition, we discover a new and universal characteristic of the second transition point-an abrupt increase of the clustering coefficient, due to formation of many small complete subgraphs inside the network.

  19. A Method for Group Extraction in Complex Social Networks

    Science.gov (United States)

    Bródka, Piotr; Musial, Katarzyna; Kazienko, Przemysław

    The extraction of social groups from social networks existing among employees in the company, its customers or users of various computer systems became one of the research areas of growing importance. Once we have discovered the groups, we can utilise them, in different kinds of recommender systems or in the analysis of the team structure and communication within a given population.

  20. How can social networks ever become complex? Modelling the emergence of complex networks from local social exchanges

    NARCIS (Netherlands)

    Pujol, Josep M.; Flache, Andreas; Delgado, Jordi; Sangüesa, Ramon; Sanguessa, R.

    2005-01-01

    Small-world and power-law network structures have been prominently proposed as models of large networks. However, the assumptions of these models usually-lack sociological grounding. We present a computational model grounded in social exchange theory. Agents search attractive exchange partners in a

  1. Complex Networks

    CERN Document Server

    Evsukoff, Alexandre; González, Marta

    2013-01-01

    In the last decade we have seen the emergence of a new inter-disciplinary field focusing on the understanding of networks which are dynamic, large, open, and have a structure sometimes called random-biased. The field of Complex Networks is helping us better understand many complex phenomena such as the spread of  deseases, protein interactions, social relationships, to name but a few. Studies in Complex Networks are gaining attention due to some major scientific breakthroughs proposed by network scientists helping us understand and model interactions contained in large datasets. In fact, if we could point to one event leading to the widespread use of complex network analysis is the availability of online databases. Theories of Random Graphs from Erdös and Rényi from the late 1950s led us to believe that most networks had random characteristics. The work on large online datasets told us otherwise. Starting with the work of Barabási and Albert as well as Watts and Strogatz in the late 1990s, we now know th...

  2. Learning to Predict Social Influence in Complex Networks

    Science.gov (United States)

    2012-03-29

    derived from the Enron Email Dataset by extracting the senders and the recipients and linking those that had bidirectional communications. It has 4,254...Kimura et al. (2008), which has 9, 481 nodes and 245, 044 directed links (the Wikipedia network). The third one is a network derived from the Enron ...It contains 4, 254 nodes and 44, 314 directed links (the Enron network). The last one is a coauthorship network employed in Palla et al. (2005). It

  3. Complex networks and computing

    Institute of Scientific and Technical Information of China (English)

    Shuigeng ZHOU; Zhongzhi ZHANG

    2009-01-01

    @@ Nowadays complex networks are pervasive in various areas of science and technology. Popular examples of complex networks include the Internet, social networks of collaboration, citations and co-authoring, as well as biological networks such as gene and protein interactions and others. Complex networks research spans across mathematics, computer science, engineering, biology and the social sciences. Even in computer science area, increasing problems are either found to be related to complex networks or studied from the perspective of complex networks, such as searching on Web and P2P networks, routing in sensor networks, language processing, software engineering etc. The interaction and mergence of complex networks and computing is inspiring new chances and challenges in computer science.

  4. Understanding the social dimension of knowledge through complex network analysis

    OpenAIRE

    Tur, E.M.

    2016-01-01

    This thesis presents five studies on the social dimension of knowledge, with a focus on its creation and diffusion processes. Broadly speaking, the creation and diffusion of knowledge are phenomena inherent to human society as a whole. In this sense, the results of the works in this thesis can be relevant and applicable in several social domains. However, the main focus of this work is on ideas rather than specific information and opinions. A working example that has been used through the cha...

  5. Rumor Spreading Model with Trust Mechanism in Complex Social Networks

    Institute of Scientific and Technical Information of China (English)

    WANG Ya-Qi; YANG Xiao-Yuan; HAN Yi-Liang; WANG Xu-An

    2013-01-01

    In this paper,to study rumor spreading,we propose a novel susceptible-infected-removed (SIR) model by introducing the trust mechanism.We derive mean-field equations that describe the dynamics of the SIR model on homogeneous networks and inhomogeneous networks.Then a steady-state analysis is conducted to investigate the critical threshold and the final size of the rumor spreading.We show that the introduction of trust mechanism reduces the final rumor size and the velocity of rumor spreading,but increases the critical thresholds on both networks.Moreover,the trust mechanism not only greatly reduces the maximum rumor influence,but also postpones the rumor terminal time,which provides us with more time to take measures to control the rumor spreading.The theoretical results are confirmed by sufficient numerical simulations.

  6. The complex social network from The Lord of The Rings

    CERN Document Server

    Ribeiro, Mauricio Aparecido; Andruchiw, Maria Larissa Pereira; Pinto, Sandro Ely de Souza

    2016-01-01

    Studies of social structures has been grown on the last years, because its sharing form and content creation attracted the public in general. Such structures are observed, as an example, in literary pieces. A featured author is J.R.R. Tolkien, with his books that describe a fictional world and its inhabitants. These books bring a narrative of the creation of the Middle-Earth and all of its mythology. His main pieces are: The Silmarillion, The Hobbit and The Lord of the rings, The objective of this article is the analysis of the social structures emerging of the conjunction of these works, where the social relations are described by the reference criteria, shared events and direct bonds, with the major centrality measures together with the structural entropy of first order. Enabling the doing of an analogy with the canonic ensemble of the mechanics statistics and enabling analyzing the degree of homogeneity of the bonds between the formed communities.

  7. Understanding the social dimension of knowledge through complex network analysis

    NARCIS (Netherlands)

    Tur, E.M.

    2016-01-01

    This thesis presents five studies on the social dimension of knowledge, with a focus on its creation and diffusion processes. Broadly speaking, the creation and diffusion of knowledge are phenomena inherent to human society as a whole. In this sense, the results of the works in this thesis can be re

  8. Understanding the social dimension of knowledge through complex network analysis

    NARCIS (Netherlands)

    Tur, E.M.

    2016-01-01

    This thesis presents five studies on the social dimension of knowledge, with a focus on its creation and diffusion processes. Broadly speaking, the creation and diffusion of knowledge are phenomena inherent to human society as a whole. In this sense, the results of the works in this thesis can be

  9. Network-oriented modeling addressing complexity of cognitive, affective and social interactions

    CERN Document Server

    Treur, Jan

    2016-01-01

    This book presents a new approach that can be applied to complex, integrated individual and social human processes. It provides an alternative means of addressing complexity, better suited for its purpose than and effectively complementing traditional strategies involving isolation and separation assumptions. Network-oriented modeling allows high-level cognitive, affective and social models in the form of (cyclic) graphs to be constructed, which can be automatically transformed into executable simulation models. The modeling format used makes it easy to take into account theories and findings about complex cognitive and social processes, which often involve dynamics based on interrelating cycles. Accordingly, it makes it possible to address complex phenomena such as the integration of emotions within cognitive processes of all kinds, of internal simulations of the mental processes of others, and of social phenomena such as shared understandings and collective actions. A variety of sample models – including ...

  10. A New Recommendation Algorithm Based on User’s Dynamic Information in Complex Social Network

    OpenAIRE

    Jiujun Cheng; Yingbo Liu; Huiting Zhang; Xiao Wu; Fuzhen Chen

    2015-01-01

    The development of recommendation system comes with the research of data sparsity, cold start, scalability, and privacy protection problems. Even though many papers proposed different improved recommendation algorithms to solve those problems, there is still plenty of room for improvement. In the complex social network, we can take full advantage of dynamic information such as user’s hobby, social relationship, and historical log to improve the performance of recommendation system. In this pa...

  11. Dissemination Of Opinions And Ideas Via Complex Contagion On Social Networks

    Science.gov (United States)

    2016-09-23

    but that cultural information needs to be transmitted accurately to maintain both coherent cultural groups and cooperation . 15. SUBJECT TERMS social ...AFRL-AFOSR-JP-TR-2016-0076 Dissemination of opinions and ideas via complex contagion on social networks Yoshihisa Kashima UNIVERSITY OF MELBOURNE...DOCUMENTATION PAGE Form ApprovedOMB No. 0704-0188 The public reporting burden for this collection of information is estimated to average 1 hour per response

  12. 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

  13. Decision dynamics in complex networks subject to mass media and social contact transmission mechanisms

    CERN Document Server

    Lucatero, Carlos Rodríguez; Jaquez, Roberto Bernal; Schaum, Alexander

    2012-01-01

    The dynamics of decisions in complex networks is studied within a Markov process framework using numerical simulations combined with mathematical insight into the process mechanisms. A mathematical discrete-time model is derived based on a set of basic assumptions on the convincing mechanisms associated to two opinions. The model is analyzed with respect to multiplicity of critical points, illustrating in this way the main behavior to be expected in the network. Particular interest is focussed on the effect of social network and exogenous mass media-based influences on the decision behavior. A set of numerical simulation results is provided illustrating how these mechanisms impact the final decision results. The analysis reveals (i) the presence of fixed-point multiplicity (with a maximum of four different fixed points), multistability, and sensitivity with respect to process parameters, and (ii) that mass media have a strong impact on the decision behavior.

  14. Reliability and efficiency of generalized rumor spreading model on complex social networks

    CERN Document Server

    Naimi, Yaghoob

    2013-01-01

    We introduce the generalized rumor spreading model and investigate some properties of this model on different complex social networks. Despite pervious rumor models that both the spreader-spreader ($SS$) and the spreader-stifler ($SR$) interactions have the same rate $\\alpha$, we define $\\alpha^{(1)}$ and $\\alpha^{(2)}$ for $SS$ and $SR$ interactions, respectively. The effect of variation of $\\alpha^{(1)}$ and $\\alpha^{(2)}$ on the final density of stiflers is investigated. Furthermore, the influence of the topological structure of the network in rumor spreading is studied by analyzing the behavior of several global parameters such as reliability and efficiency. Our results show that while networks with homogeneous connectivity patterns reach a higher reliability, scale-free topologies need a less time to reach a steady state with respect the rumor.

  15. Reliability and Efficiency of Generalized Rumor Spreading Model on Complex Social Networks

    Institute of Scientific and Technical Information of China (English)

    Yaghoob Naimi; Mohammad Naimi

    2013-01-01

    We introduce the generalized rumor spreading model and investigate some properties of this model on different complex social networks.Despite pervious rumor models that both the spreader-spreader (SS) and the spreaderstifler (SR) interactions have the same rate α,we define α(1) and α(2) for SS and SR interactions,respectively.The effect of variation of α(1) and α(2) on the final density of stiflers is investigated.Furthermore,the influence of the topological structure of the network in rumor spreading is studied by analyzing the behavior of several global parameters such as reliability and efficiency.Our results show that while networks with homogeneous connectivity patterns reach a higher reliability,scale-free topologies need a less time to reach a steady state with respect the rumor.

  16. Predicting human preferences using the block structure of complex social networks

    CERN Document Server

    Guimera, Roger; Moro, Esteban; Sales-Pardo, Marta; 10.1371/journal.pone.0044620

    2012-01-01

    With ever-increasing available data, predicting individuals' preferences and helping them locate the most relevant information has become a pressing need. Understanding and predicting preferences is also important from a fundamental point of view, as part of what has been called a "new" computational social science. Here, we propose a novel approach based on stochastic block models, which have been developed by sociologists as plausible models of complex networks of social interactions. Our model is in the spirit of predicting individuals' preferences based on the preferences of others but, rather than fitting a particular model, we rely on a Bayesian approach that samples over the ensemble of all possible models. We show that our approach is considerably more accurate than leading recommender algorithms, with major relative improvements between 38% and 99% over industry-level algorithms. Besides, our approach sheds light on decision-making processes by identifying groups of individuals that have consistently...

  17. The Analysis of Social Networks.

    Science.gov (United States)

    O'Malley, A James; Marsden, Peter V

    2008-12-01

    Many questions about the social organization of medicine and health services involve interdependencies among social actors that may be depicted by networks of relationships. Social network studies have been pursued for some time in social science disciplines, where numerous descriptive methods for analyzing them have been proposed. More recently, interest in the analysis of social network data has grown among statisticians, who have developed more elaborate models and methods for fitting them to network data. This article reviews fundamentals of, and recent innovations in, social network analysis using a physician influence network as an example. After introducing forms of network data, basic network statistics, and common descriptive measures, it describes two distinct types of statistical models for network data: individual-outcome models in which networks enter the construction of explanatory variables, and relational models in which the network itself is a multivariate dependent variable. Complexities in estimating both types of models arise due to the complex correlation structures among outcome measures.

  18. Synchronization in complex networks

    Energy Technology Data Exchange (ETDEWEB)

    Arenas, A.; Diaz-Guilera, A.; Moreno, Y.; Zhou, C.; Kurths, J.

    2007-12-12

    Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analytical approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.

  19. Complex Networks approach to modeling online social systems: The emergence of computational social science

    OpenAIRE

    2013-01-01

    La presente tesis está dedicada a la descripción, análisis y modelado cuantitativo de sistemas complejos sociales en forma de redes sociales en internet. Mediante el uso de métodos y conceptos provenientes de ciencia de redes, análisis de redes sociales y minería de datos se descubren diferentes patrones estadísticos de los sistemas estudiados. Uno de los objetivos a largo plazo de esta línea de investigación consiste en hacer posible la predicción del comportamiento de sistemas complejos te...

  20. A New Recommendation Algorithm Based on User’s Dynamic Information in Complex Social Network

    Directory of Open Access Journals (Sweden)

    Jiujun Cheng

    2015-01-01

    Full Text Available The development of recommendation system comes with the research of data sparsity, cold start, scalability, and privacy protection problems. Even though many papers proposed different improved recommendation algorithms to solve those problems, there is still plenty of room for improvement. In the complex social network, we can take full advantage of dynamic information such as user’s hobby, social relationship, and historical log to improve the performance of recommendation system. In this paper, we proposed a new recommendation algorithm which is based on social user’s dynamic information to solve the cold start problem of traditional collaborative filtering algorithm and also considered the dynamic factors. The algorithm takes user’s response information, dynamic interest, and the classic similar measurement of collaborative filtering algorithm into account. Then, we compared the new proposed recommendation algorithm with the traditional user based collaborative filtering algorithm and also presented some of the findings from experiment. The results of experiment demonstrate that the new proposed algorithm has a better recommended performance than the collaborative filtering algorithm in cold start scenario.

  1. Advances in network complexity

    CERN Document Server

    Dehmer, Matthias; Emmert-Streib, Frank

    2013-01-01

    A well-balanced overview of mathematical approaches to describe complex systems, ranging from chemical reactions to gene regulation networks, from ecological systems to examples from social sciences. Matthias Dehmer and Abbe Mowshowitz, a well-known pioneer in the field, co-edit this volume and are careful to include not only classical but also non-classical approaches so as to ensure topicality. Overall, a valuable addition to the literature and a must-have for anyone dealing with complex systems.

  2. Dynamics on and of complex networks applications to biology, computer science, and the social sciences

    CERN Document Server

    Ganguly, Niloy; Mukherjee, Animesh

    2009-01-01

    This self-contained book systematically explores the statistical dynamics on and of complex networks having relevance across a large number of scientific disciplines. The theories related to complex networks are increasingly being used by researchers for their usefulness in harnessing the most difficult problems of a particular discipline. The book is a collection of surveys and cutting-edge research contributions exploring the interdisciplinary relationship of dynamics on and of complex networks. Towards this goal, the work is thematically organized into three main sections: Part I studies th

  3. 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...

  4. 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.

  5. Emergent Complex Behavior in Social Networks: Examples from the Ktunaxa Speech Community

    Science.gov (United States)

    Horsethief, Christopher

    2012-01-01

    Language serves as a primary tool for structuring identity and loss of language represents the loss of that identity. This study utilizes a social network analysis of Ktunaxa speech community activities for evidence of internally generated revitalization efforts. These behaviors include instances of self-organized emergence. Such emergent behavior…

  6. El complejo mundo de la interactividad: emociones y redes sociales The complex world of interactivity: emotions and social networks

    Directory of Open Access Journals (Sweden)

    Lourdes Sánchez Martín

    2011-07-01

    Full Text Available El objetivo de la presente investigación es discernir cómo debe plantearse un aprendizaje en nuevas tecnologías, en especial, en redes sociales. Para esto, se analizará la dinámica neurológica y psicológica de las emociones y cómo se desenvuelven en el ámbito de las redes sociales. La metodología que emplearemos será acudir a diversos estudios neurológicos y psicológicos actuales, en especial de Antonio Damasio, para analizar posteriormente qué sucede con las emociones cuando nos comunicamos a través de redes sociales, tomando como referente un experimento neurológico de dicho autor en el cerebro de varios voluntarios que muestra la aparición de diversos tipos de emociones. Por último, extrapolaremos este experimento a la aparición de emociones si se utiliza como medio de comunicación las redes sociales y realizaremos algunas conclusiones acerca de la dirección a la que debe tender el aprendizaje de nuevas tecnologías, en especial, redes sociales, teniendo en cuenta dichas observaciones.The objective of this research is to discern how it should consider learning on new technologies, especially in social networks. For this, we examine the neurological and psychological dynamics of emotions and how they develop in the field of social networks. Our methodology will go to various neurological and psychological studies today, including Antonio Damasio and how to analyze what happens when we communicate emotions through social networks, by reference to a neurological experiment that copyright in the brain several volunteers that shows the appearance of various types of emotions. Finally, we extrapolate this experiment to the appearance of emotions when social networks are used as media and will make some conclusions about the direction you should aim to learn new technologies, especially social networks, taking into account such observations.

  7. 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

  8. Complex networks theory for analyzing metabolic networks

    Institute of Scientific and Technical Information of China (English)

    ZHAO Jing; YU Hong; LUO Jianhua; CAO Z.W.; LI Yixue

    2006-01-01

    One of the main tasks of post-genomic informatics is to systematically investigate all molecules and their interactions within a living cell so as to understand how these molecules and the interactions between them relate to the function of the organism,while networks are appropriate abstract description of all kinds of interactions. In the past few years, great achievement has been made in developing theory of complex networks for revealing the organizing principles that govern the formation and evolution of various complex biological, technological and social networks. This paper reviews the accomplishments in constructing genome-based metabolic networks and describes how the theory of complex networks is applied to analyze metabolic networks.

  9. Wayfinding in Social Networks

    Science.gov (United States)

    Liben-Nowell, David

    With the recent explosion of popularity of commercial social-networking sites like Facebook and MySpace, the size of social networks that can be studied scientifically has passed from the scale traditionally studied by sociologists and anthropologists to the scale of networks more typically studied by computer scientists. In this chapter, I will highlight a recent line of computational research into the modeling and analysis of the small-world phenomenon - the observation that typical pairs of people in a social network are connected by very short chains of intermediate friends - and the ability of members of a large social network to collectively find efficient routes to reach individuals in the network. I will survey several recent mathematical models of social networks that account for these phenomena, with an emphasis on both the provable properties of these social-network models and the empirical validation of the models against real large-scale social-network data.

  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......Multilayer networks, in particular multilayer social networks, where users belong to and interact on different networks at the same time, are an active research area in social network analysis, computer science, and physics. These networks have traditionally been studied within these separate...

  11. Language Networks as Complex Systems

    Science.gov (United States)

    Lee, Max Kueiming; Ou, Sheue-Jen

    2008-01-01

    Starting in the late eighties, with a growing discontent with analytical methods in science and the growing power of computers, researchers began to study complex systems such as living organisms, evolution of genes, biological systems, brain neural networks, epidemics, ecology, economy, social networks, etc. In the early nineties, the research…

  12. Impact of Social Reward on the Evolution of the Cooperation Behavior in Complex Networks

    Science.gov (United States)

    Wu, Yu’e; Chang, Shuhua; Zhang, Zhipeng; Deng, Zhenghong

    2017-01-01

    Social reward, as a significant mechanism explaining the evolution of cooperation, has attracted great attention both theoretically and experimentally. In this paper, we study the evolution of cooperation by proposing a reward model in network population, where a third strategy, reward, as an independent yet particular type of cooperation is introduced in 2-person evolutionary games. Specifically, a new kind of role corresponding to reward strategy, reward agents, is defined, which is aimed at increasing the income of cooperators by applying to them a social reward. Results from numerical simulations show that consideration of social reward greatly promotes the evolution of cooperation, which is confirmed for different network topologies and two evolutionary games. Moreover, we explore the microscopic mechanisms for the promotion of cooperation in the three-strategy model. As expected, the reward agents play a vital role in the formation of cooperative clusters, thus resisting the aggression of defectors. Our research might provide valuable insights into further exploring the nature of cooperation in the real world. PMID:28112276

  13. Impact of Social Reward on the Evolution of the Cooperation Behavior in Complex Networks

    Science.gov (United States)

    Wu, Yu’E.; Chang, Shuhua; Zhang, Zhipeng; Deng, Zhenghong

    2017-01-01

    Social reward, as a significant mechanism explaining the evolution of cooperation, has attracted great attention both theoretically and experimentally. In this paper, we study the evolution of cooperation by proposing a reward model in network population, where a third strategy, reward, as an independent yet particular type of cooperation is introduced in 2-person evolutionary games. Specifically, a new kind of role corresponding to reward strategy, reward agents, is defined, which is aimed at increasing the income of cooperators by applying to them a social reward. Results from numerical simulations show that consideration of social reward greatly promotes the evolution of cooperation, which is confirmed for different network topologies and two evolutionary games. Moreover, we explore the microscopic mechanisms for the promotion of cooperation in the three-strategy model. As expected, the reward agents play a vital role in the formation of cooperative clusters, thus resisting the aggression of defectors. Our research might provide valuable insights into further exploring the nature of cooperation in the real world.

  14. The model of microblog message diffusion based on complex social network

    Science.gov (United States)

    Zhang, Wei; Bai, Shu-Ying; Jin, Rui

    2014-05-01

    Microblog is a micromessage communication network in which users are the nodes and the followship between users are the edges. Sina Weibo is a typical case of these microblog service websites. As the enormous scale of nodes and complex links in the network, we choose a sample network crawled in Sina Weibo as the base of empirical analysis. The study starts with the analysis of its topological features, and brings in epidemiological SEIR model to explore the mode of message spreading throughout the microblog network. It is found that the network is obvious small-world and scale-free, which made it succeed in transferring messages and failed in resisting negative influence. In addition, the paper focuses on the rich nodes as they constitute a typical feature of Sina Weibo. It is also found that whether the message starts with a rich node will not account for its final coverage. Actually, the rich nodes always play the role of pivotal intermediaries who speed up the spreading and make the message known by much more people.

  15. On convexity in complex networks

    CERN Document Server

    Marc, Tilen

    2016-01-01

    Metric graph properties lie in the heart of the analysis of complex networks, while in this paper we study their convexity. We analyze the expansion of convex subsets of nodes in empirical networks and also convexity of small subgraphs known as graphlets. We demonstrate that convexity is an inherent property of complex networks not present in a random graph. According to our perception of convexity, a convex network is such in which every connected subset of nodes induces a convex subgraph. Especially convex are technological networks and social collaboration graphs, whereas food webs are the only networks studied that are truly non-convex. Many other networks can be divided into a non-convex core surrounded by a convex periphery. We interpret convexity in terms of redundancy of shortest paths in a network and discuss possible applications.

  16. Social networks in supervision

    DEFF Research Database (Denmark)

    Lystbæk, Christian Tang

    and practice have focused on conceptual frameworks and practical techniques of promoting reflection through conversation in general and questioning in particular. However, in recent years, supervision research has started to focus on the social and technological aspects of supervision. This calls...... is constituted by the relationality of the actors, not by the actors themselves. In other words, no one acts in a vacuum but rather always under the influence of a wide range of surrounding and interconnected factors. Actors are actors because they are in a networked relationship. Thus, focusing on social...... and space. That involves mobilised an denrolled actos, both animate and inanimate (e.g. books, computers, etc. Actor-network theory defines a symmetry between animate and inanimate, i.e. subjects and objects, because ”human powers increasingly derive from the complex interconnections if human with material...

  17. Characteristic exponents of complex networks

    CERN Document Server

    Nicosia, Vincenzo; Latora, Vito

    2013-01-01

    We propose a method to characterize and classify complex networks based on the time series generated by random walks and different node properties. The analysis of the fluctuations of the time series reveals the presence of long-range correlations, and allows to define, for each network, a set of characteristic exponents that capture its essential structural properties. By considering a large data set of real-world networks, we show that the characteristic exponents can be used to classify complex networks according to their function, and are able to discriminate social from biological and technological systems.

  18. A novel mammalian social structure in Indo-Pacific bottlenose dolphins (Tursiops sp.): complex male alliances in an open social network.

    Science.gov (United States)

    Randić, Srđan; Connor, Richard C; Sherwin, William B; Krützen, Michael

    2012-08-01

    Terrestrial mammals with differentiated social relationships live in 'semi-closed groups' that occasionally accept new members emigrating from other groups. Bottlenose dolphins (Tursiops sp.) in Shark Bay, Western Australia, exhibit a fission-fusion grouping pattern with strongly differentiated relationships, including nested male alliances. Previous studies failed to detect a group membership 'boundary', suggesting that the dolphins live in an open social network. However, two alternative hypotheses have not been excluded. The community defence model posits that the dolphins live in a large semi-closed 'chimpanzee-like' community defended by males and predicts that a dominant alliance(s) will range over the entire community range. The mating season defence model predicts that alliances will defend mating-season territories or sets of females. Here, both models are tested and rejected: no alliances ranged over the entire community range and alliances showed extensive overlap in mating season ranges and consorted females. The Shark Bay dolphins, therefore, present a combination of traits that is unique among mammals: complex male alliances in an open social network. The open social network of dolphins is linked to their relatively low costs of locomotion. This reveals a surprising and previously unrecognized convergence between adaptations reducing travel costs and complex intergroup-alliance relationships in dolphins, elephants and humans.

  19. 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.

  20. Weak Links: Stabilizers of Complex Systems from Proteins to Social Networks

    Science.gov (United States)

    Csermely, Peter

    Why do women stabilize our societies? Why can we enjoy and understand Shakespeare? Why are fruitflies uniform? Why do omnivorous eating habits aid our survival? Why is Mona Lisa's smile beautiful? -- Is there any answer to these questions? This book shows that the statement: "weak links stabilize complex systems" holds the answers to all of the surprising questions above. The author (recipientof several distinguished science communication prizes) uses weak (low affinity, low probability) interactions as a thread to introduce a vast varietyof networks from proteins to ecosystems.

  1. Economia Informal em Rede: trocas económicas e complexidade social Informal economy network: economic exchanges and social complexity

    Directory of Open Access Journals (Sweden)

    Marzia Grassi

    2012-03-01

    Full Text Available Partindo das realidades empíricas de Cabo Verde e diásporas, este texto explora, até certo ponto, as limitações heurísticas de certas noções sugeridas pela mainstream do modelo neoliberal da economia sobre o «informal» em África. O texto debruça-se sobre diferentes dimensões, espaços e protagonistas de práticas de economia informal em rede. As repercussões identitárias das dinâmicas destas redes entre os cabo-verdianos, apreendidas através da observação de certas formas de sociabilidade dos actores sociais considerados, são igualmente exploradas.Based on the empirical realities of Cape Verde and some of its Diasporas, this article explores, to a certain extent, the heuristic limitations of certain notions suggested by the mainstream of the neoliberal economy model concerning the so called «informal economy» in Africa. The text deals with different dimensions, spaces and protagonists of practices of the informal economic networks. The identitarian repercussions of the dynamics of these networks among Capeverdians, apprehended through the observation of certain forms of socialibility of these social actors are also explored.

  2. Epidemic and Cascading Survivability of Complex Networks

    DEFF Research Database (Denmark)

    Manzano, Marc; Calle, Eusebi; Ripoll, Jordi

    2014-01-01

    Our society nowadays is governed by complex networks, examples being the power grids, telecommunication networks, biological networks, and social networks. It has become of paramount importance to understand and characterize the dynamic events (e.g. failures) that might happen in these complex...

  3. Next Generation Social Networks

    DEFF Research Database (Denmark)

    Sørensen, Lene Tolstrup; Skouby, Knud Erik

    2008-01-01

    When it comes to discussing the future of electronic communication, social networking is the buzzword. The Internet has become a platform where new social networks emerge and the Internet it itself support the more traditional computer supported communication. The way users build and verifies...... 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. Emergent Complex Network Geometry

    CERN Document Server

    Wu, Zhihao; Rahmede, Christoph; Bianconi, Ginestra

    2014-01-01

    Networks are mathematical structures that are universally used to describe a large variety of complex systems such as the brain or the Internet. Characterizing the geometrical properties of these networks has become increasingly relevant for routing problems, inference and data mining. In real growing networks, topological, structural and geometrical properties emerge spontaneously from their dynamical rules. Nevertheless we still miss a model in which networks develop an emergent complex geometry. Here we show that a single two parameter network model, the growing geometrical network, can generate complex network geometries with non-trivial distribution of curvatures, combining exponential growth and small-world properties with finite spectral dimensionality. In one limit, the non-equilibrium dynamical rules of these networks can generate scale-free networks with clustering and communities, in another limit planar random geometries with non-trivial modularity. Finally we find that these properties of the geo...

  5. 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.

  6. Social network analysis

    OpenAIRE

    Mathias, Carlos Leonardo Kelmer

    2014-01-01

    In general, the paper develops a historiographical debate about the methodology of social network analysis. More than responding questions using such methodology, this article tries to introduce the historian to the founder bibliography of social network analysis. Since the publication of the famous article by John Barnes in 1954, sociologists linked to sociometric studies have usually employed the social network analysis in their studies. On the other hand, this methodology is not widespread...

  7. Marketing on social networks

    OpenAIRE

    Kadečková, Anna

    2016-01-01

    The bachelor´s thesis is focused on marketing communications on social networks in recruitment agency OPENN. The work is composed of three parts: literature review, own work and draft recommendations. The first part describes the basic concepts of marketing, marketing mix and communication mix, whose tools are used to successful marketing on social networks. Among other things, thesis informs on major social networks, including Facebook, Twitter, LinkedIn, Google+, YouTube and Instagram. It f...

  8. Network Complexity of Foodwebs

    CERN Document Server

    Standish, Russell K

    2010-01-01

    In previous work, I have developed an information theoretic complexity measure of networks. When applied to several real world food webs, there is a distinct difference in complexity between the real food web, and randomised control networks obtained by shuffling the network links. One hypothesis is that this complexity surplus represents information captured by the evolutionary process that generated the network. In this paper, I test this idea by applying the same complexity measure to several well-known artificial life models that exhibit ecological networks: Tierra, EcoLab and Webworld. Contrary to what was found in real networks, the artificial life generated foodwebs had little information difference between itself and randomly shuffled versions.

  9. Symmetry in Complex Networks

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2011-01-01

    Full Text Available In this paper, we analyze a few interrelated concepts about graphs, such as their degree, entropy, or their symmetry/asymmetry levels. These concepts prove useful in the study of different types of Systems, and particularly, in the analysis of Complex Networks. A System can be defined as any set of components functioning together as a whole. A systemic point of view allows us to isolate a part of the world, and so, we can focus on those aspects that interact more closely than others. Network Science analyzes the interconnections among diverse networks from different domains: physics, engineering, biology, semantics, and so on. Current developments in the quantitative analysis of Complex Networks, based on graph theory, have been rapidly translated to studies of brain network organization. The brain's systems have complex network features—such as the small-world topology, highly connected hubs and modularity. These networks are not random. The topology of many different networks shows striking similarities, such as the scale-free structure, with the degree distribution following a Power Law. How can very different systems have the same underlying topological features? Modeling and characterizing these networks, looking for their governing laws, are the current lines of research. So, we will dedicate this Special Issue paper to show measures of symmetry in Complex Networks, and highlight their close relation with measures of information and entropy.

  10. Interpreting participatory Fuzzy Cognitive Maps as complex networks in the social-ecological systems of the Amazonian forests

    Science.gov (United States)

    Varela, Consuelo; Tarquis, Ana M.; Blanco-Gutiérrez, Irene; Estebe, Paloma; Toledo, Marisol; Martorano, Lucieta

    2015-04-01

    Social-ecological systems are linked complex systems that represent interconnected human and biophysical processes evolving and adapting across temporal and spatial scales. In the real world, social-ecological systems pose substantial challenges for modeling. In this regard, Fuzzy Cognitive Maps (FCMs) have proven to be a useful method for capturing the functioning of this type of systems. FCMs are a semi-quantitative type of cognitive map that represent a system composed of relevant factors and weighted links showing the strength and direction of cause-effects relationships among factors. Therefore, FCMs can be interpreted as complex system structures or complex networks. In this sense, recent research has applied complex network concepts for the analysis of FCMs that represent social-ecological systems. Key to FCM the tool is its potential to allow feedback loops and to include stakeholder knowledge in the construction of the tool. Also, previous research has demonstrated their potential to represent system dynamics and simulate the effects of changes in the system, such as policy interventions. For illustrating this analysis, we have developed a series of participatory FCM for the study of the ecological and human systems related to biodiversity conservation in two case studies of the Amazonian region, the Bolivia lowlands of Guarayos and the Brazil Tapajos National forest. The research is carried out in the context of the EU project ROBIN1 and it is based on the development of a series of stakeholder workshops to analyze the current state of the socio-ecological environment in the Amazonian forest, reflecting conflicts and challenges for biodiversity conservation and human development. Stakeholders included all relevant actors in the local case studies, namely farmers, environmental groups, producer organizations, local and provincial authorities and scientists. In both case studies we illustrate the use of complex networks concepts, such as the adjacency

  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. Evolution of Social networks

    OpenAIRE

    Hellmann, Tim; Staudigl, Mathias

    2012-01-01

    Modeling the evolution of networks is central to our understanding of modern large communication systems, such as theWorld-Wide-Web, as well as economic and social networks. The research on social and economic networks is truly interdisciplinary and the number of modeling strategies and concepts is enormous. In this survey we present some modeling approaches, covering classical random graph models and game-theoretic models, which may be used to provide a unified framework to model and analyze...

  13. Benford's Distribution in Complex Networks.

    Science.gov (United States)

    Morzy, Mikołaj; Kajdanowicz, Tomasz; Szymański, Bolesław K

    2016-10-17

    Many collections of numbers do not have a uniform distribution of the leading digit, but conform to a very particular pattern known as Benford's distribution. This distribution has been found in numerous areas such as accounting data, voting registers, census data, and even in natural phenomena. Recently it has been reported that Benford's law applies to online social networks. Here we introduce a set of rigorous tests for adherence to Benford's law and apply it to verification of this claim, extending the scope of the experiment to various complex networks and to artificial networks created by several popular generative models. Our findings are that neither for real nor for artificial networks there is sufficient evidence for common conformity of network structural properties with Benford's distribution. We find very weak evidence suggesting that three measures, degree centrality, betweenness centrality and local clustering coefficient, could adhere to Benford's law for scalefree networks but only for very narrow range of their parameters.

  14. "Conjectural" links in complex networks

    Science.gov (United States)

    Snarskii, A. A.; Zorinets, D. I.; Lande, D. V.

    2016-11-01

    This paper introduces the concept of Conjectural Link for Complex Networks, in particular, social networks. Conjectural Link we understand as an implicit link, not available in the network, but supposed to be present, based on the characteristics of its topology. It is possible, for example, when in the formal description of the network some connections are skipped due to errors, deliberately hidden or withdrawn (e.g. in the case of partial destruction of the network). Introduced a parameter that allows ranking the Conjectural Link. The more this parameter - the more likely that this connection should be present in the network. This paper presents a method of recovery of partially destroyed Complex Networks using Conjectural Links finding. Presented two methods of finding the node pairs that are not linked directly to one another, but have a great possibility of Conjectural Link communication among themselves: a method based on the determination of the resistance between two nodes, and method based on the computation of the lengths of routes between two nodes. Several examples of real networks are reviewed and performed a comparison to know network links prediction methods, not intended to find the missing links in already formed networks.

  15. 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

  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. Resilience of modular complex networks

    CERN Document Server

    Shai, Saray; Kenett, Yoed N; Faust, Miriam; Dobson, Simon; Havlin, Shlomo

    2014-01-01

    Complex networks often have a modular structure, where a number of tightly- connected groups of nodes (modules) have relatively few interconnections. Modularity had been shown to have an important effect on the evolution and stability of biological networks, on the scalability and efficiency of large-scale infrastructure, and the development of economic and social systems. An analytical framework for understanding modularity and its effects on network vulnerability is still missing. Through recent advances in the understanding of multilayer networks, however, it is now possible to develop a theoretical framework to systematically study this critical issue. Here we study, analytically and numerically, the resilience of modular networks under attacks on interconnected nodes, which exhibit high betweenness values and are often more exposed to failure. Our model provides new understandings into the feedback between structure and function in real world systems, and consequently has important implications as divers...

  18. Synchronization in complex clustered networks

    Institute of Scientific and Technical Information of China (English)

    HUANG Liang; LAI Ying-Cheng; Kwangho PARK; WANG Xingang; LAI Choy Heng; Robert A. GATENBY

    2007-01-01

    Synchronization in complex networks has been an active area of research in recent years. While much effort has been devoted to networks with the small-world and scale-free topology, structurally they are often assumed to have a single, densely connected component. Recently it has also become apparent that many networks in social, biological, and tech-nological systems are clustered, as characterized by a number (or a hierarchy) of sparsely linked clusters, each with dense and complex internal connections. Synchronization is funda-mental to the dynamics and functions of complex clustered networks, but this problem has just begun to be addressed. This paper reviews some progress in this direction by focus-ing on the interplay between the clustered topology and net-work synchronizability. In particular, there are two parame-ters characterizing a clustered network: the intra-cluster and the inter-cluster link density. Our goal is to clarify the roles of these parameters in shaping network synchronizability. By using theoretical analysis and direct numerical simulations of oscillator networks, it is demonstrated that clustered net-works with random inter-cluster links are more synchroniz-able, and synchronization can be optimized when inter-cluster and intra-cluster links match. The latter result has one coun-terintuitive implication: more links, if placed improperly, can actually lead to destruction of synchronization, even though such links tend to decrease the average network distance. It is hoped that this review will help attract attention to the fun-damental problem of clustered structures/synchronization in network science.

  19. 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......Social networks are a key contributor to the economic and social fabric of life. There is evidence that the social cohesion that social networks provide is critical for societies to prosper economically and for development to be sustainable. These social networks and the functions they perform co......-exist with, influence and are influenced by the business networks of connected firms and other economic organisations that surround them. This is increasingly so in our ever-more-complex, internationalized and connected world. This paper explores the potential consequences of this influence via a case study...

  20. Affinity driven social networks

    Science.gov (United States)

    Ruyú, B.; Kuperman, M. N.

    2007-04-01

    In this work we present a model for evolving networks, where the driven force is related to the social affinity between individuals of a population. In the model, a set of individuals initially arranged on a regular ordered network and thus linked with their closest neighbors are allowed to rearrange their connections according to a dynamics closely related to that of the stable marriage problem. We show that the behavior of some topological properties of the resulting networks follows a non trivial pattern.

  1. Social network analysis

    NARCIS (Netherlands)

    W. de Nooy

    2009-01-01

    Social network analysis (SNA) focuses on the structure of ties within a set of social actors, e.g., persons, groups, organizations, and nations, or the products of human activity or cognition such as web sites, semantic concepts, and so on. It is linked to structuralism in sociology stressing the si

  2. Spreading dynamics in complex networks

    CERN Document Server

    Pei, Sen

    2013-01-01

    Searching for influential spreaders in complex networks is an issue of great significance for applications across various domains, ranging from the epidemic control, innovation diffusion, viral marketing, social movement to idea propagation. In this paper, we first display some of the most important theoretical models that describe spreading processes, and then discuss the problem of locating both the individual and multiple influential spreaders respectively. Recent approaches in these two topics are presented. For the identification of privileged single spreaders, we summarize several widely used centralities, such as degree, betweenness centrality, PageRank, k-shell, etc. We investigate the empirical diffusion data in a large scale online social community -- LiveJournal. With this extensive dataset, we find that various measures can convey very distinct information of nodes. Of all the users in LiveJournal social network, only a small fraction of them involve in spreading. For the spreading processes in Li...

  3. Interests Diffusion in Social Networks

    CERN Document Server

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

    2015-01-01

    Understanding cultural phenomena on Social Networks (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 p...

  4. Complex Semantic Networks

    Science.gov (United States)

    Teixeira, G. M.; Aguiar, M. S. F.; Carvalho, C. F.; Dantas, D. R.; Cunha, M. V.; Morais, J. H. M.; Pereira, H. B. B.; Miranda, J. G. V.

    Verbal language is a dynamic mental process. Ideas emerge by means of the selection of words from subjective and individual characteristics throughout the oral discourse. The goal of this work is to characterize the complex network of word associations that emerge from an oral discourse from a discourse topic. Because of that, concepts of associative incidence and fidelity have been elaborated and represented the probability of occurrence of pairs of words in the same sentence in the whole oral discourse. Semantic network of words associations were constructed, where the words are represented as nodes and the edges are created when the incidence-fidelity index between pairs of words exceeds a numerical limit (0.001). Twelve oral discourses were studied. The networks generated from these oral discourses present a typical behavior of complex networks and their indices were calculated and their topologies characterized. The indices of these networks obtained from each incidence-fidelity limit exhibit a critical value in which the semantic network has maximum conceptual information and minimum residual associations. Semantic networks generated by this incidence-fidelity limit depict a pattern of hierarchical classes that represent the different contexts used in the oral discourse.

  5. 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.

  6. 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.

  7. Epidemic processes in complex networks

    Science.gov (United States)

    Pastor-Satorras, Romualdo; Castellano, Claudio; Van Mieghem, Piet; Vespignani, Alessandro

    2015-07-01

    In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.

  8. Evolution model of online social networks based on complex networks%复杂网络中的在线社交网络演化模型

    Institute of Scientific and Technical Information of China (English)

    王景丽; 许立波; 庞超逸

    2015-01-01

    在线社交网络是一种广泛存在的社会网络,其节点度遵循幂率分布规律,但对于其结构演化模型方面的相关研究还不多. 基于复杂网络理论研究在线社交网络内部结构特征,提出一种结合内增长、外增长及内部边更替的演化模型,借助平均场理论分析该模型的拓扑特性,实验和理论分析表明由该模型生成的网络,其度分布服从幂率分布,且通过调整参数,幂率指数在1~3,能较好地反映不同类型的真实在线社交网络的度分布特征,因此具有广泛适用性.%As a widespread social network , the node degree of online social networks has been proven by many re-searchers to follow the power-law distribution .However , there are few studies modeling the evolution of its struc-ture.In this paper , we propose an evolution model that combines the inside growth , outside growth , and edge re-placement based on those of complex networks .The topology properties of this model are analyzed using the mean-field theory .Experiment and theoretical analyses show that the degree of a node in a network generated by the new evolution model follows the power-law distribution and that the power-law index ranges between 1 and 3.Therefore , the proposed model can better reflect the node degree distribution characteristics of different types of real online so -cial networks and will have wide applicability .

  9. Sensitivity of Complex Networks

    CERN Document Server

    Angulo, Marco Tulio; Liu, Yang-Yu; Barabási, Albert-László

    2016-01-01

    The sensitivity (i.e. dynamic response) of complex networked systems has not been well understood, making difficult to predict whether new macroscopic dynamic behavior will emerge even if we know exactly how individual nodes behave and how they are coupled. Here we build a framework to quantify the sensitivity of complex networked system of coupled dynamic units. We characterize necessary and sufficient conditions for the emergence of new macroscopic dynamic behavior in the thermodynamic limit. We prove that these conditions are satisfied only for architectures with power-law degree distributions. Surprisingly, we find that highly connected nodes (i.e. hubs) only dominate the sensitivity of the network up to certain critical frequency.

  10. Quantum social networks

    CERN Document Server

    Cabello, Adan; Lopez-Tarrida, Antonio J; Portillo, Jose R

    2011-01-01

    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 is used to measure whether the interactions originating a SN obey pre-existing properties, as in a classical social network (CSN). As an example of SNs beyond CSNs, we introduce quantum social networks (QSNs) as those in which actor $i$ is characterized by a test of whether or not the system is in a quantum state $|\\psi_i>$. 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.

  11. A Logic for Diffusion in Social Networks

    NARCIS (Netherlands)

    Christoff, Z.; Hansen, J.U.

    2015-01-01

    This paper introduces a general logical framework for reasoning about diffusion processes within social networks. The new "Logic for Diffusion in Social Networks" is a dynamic extension of standard hybrid logic, allowing to model complex phenomena involving several properties of agents. We provide a

  12. Social Network Infiltration

    Science.gov (United States)

    Plait, Philip

    2008-05-01

    Social networks are websites (or software that distributes media online) where users can distribute content to either a list of friends on that site or to anyone who surfs onto their page, and where those friends can interact and discuss the content. By linking to friends online, the users’ personal content (pictures, songs, favorite movies, diaries, websites, and so on) is dynamically distributed, and can "become viral", that is, get spread rapidly as more people see it and spread it themselves. Social networks are immensely popular around the planet, especially with younger users. The biggest social networks are Facebook and MySpace; an IYA2009 user already exists on Facebook, and one will be created for MySpace (in fact, several NASA satellites such as GLAST and Swift already have successful MySpace pages). Twitter is another network where data distribution is more limited; it is more like a mini-blog, but is very popular. IYA2009 already has a Twitter page, and will be updated more often with relevant information. In this talk I will review the existing social networks, show people how and why they are useful, and give them the tools they need to contribute meaningfully to IYA's online reach.

  13. Complexity of Public Transport Networks

    Institute of Scientific and Technical Information of China (English)

    LU Huapu; SHI Ye

    2007-01-01

    The theory of complex networks was used to classify public transport networks into public transportation route networks, public transportation transfer networks, and bus station networks. The practical significance of the network parameters was then analyzed. The public transport networks in Langfang, Jining, and Dalian were then chosen as specific research cases. The results show that the public transportation networks have the characteristics of complex networks. In addition, the urban transportation network parameters all significantly affect the accessibility, convenience, and terrorist security capability of the urban public transportation network. The results link the findings with the actual situations to explore means to solve transportation system problems.

  14. Contagion on complex networks with persuasion

    Science.gov (United States)

    Huang, Wei-Min; Zhang, Li-Jie; Xu, Xin-Jian; Fu, Xinchu

    2016-03-01

    The threshold model has been widely adopted as a classic model for studying contagion processes on social networks. We consider asymmetric individual interactions in social networks and introduce a persuasion mechanism into the threshold model. Specifically, we study a combination of adoption and persuasion in cascading processes on complex networks. It is found that with the introduction of the persuasion mechanism, the system may become more vulnerable to global cascades, and the effects of persuasion tend to be more significant in heterogeneous networks than those in homogeneous networks: a comparison between heterogeneous and homogeneous networks shows that under weak persuasion, heterogeneous networks tend to be more robust against random shocks than homogeneous networks; whereas under strong persuasion, homogeneous networks are more stable. Finally, we study the effects of adoption and persuasion threshold heterogeneity on systemic stability. Though both heterogeneities give rise to global cascades, the adoption heterogeneity has an overwhelmingly stronger impact than the persuasion heterogeneity when the network connectivity is sufficiently dense.

  15. Epidemic and Cascading Survivability of Complex Networks

    CERN Document Server

    Manzano, Marc; Ripoll, Jordi; Fagertun, Anna Manolova; Torres-Padrosa, Victor; Pahwa, Sakshi; Scoglio, Caterina

    2014-01-01

    Our society nowadays is governed by complex networks, examples being the power grids, telecommunication networks, biological networks, and social networks. It has become of paramount importance to understand and characterize the dynamic events (e.g. failures) that might happen in these complex networks. For this reason, in this paper, we propose two measures to evaluate the vulnerability of complex networks in two different dynamic multiple failure scenarios: epidemic-like and cascading failures. Firstly, we present \\emph{epidemic survivability} ($ES$), a new network measure that describes the vulnerability of each node of a network under a specific epidemic intensity. Secondly, we propose \\emph{cascading survivability} ($CS$), which characterizes how potentially injurious a node is according to a cascading failure scenario. Then, we show that by using the distribution of values obtained from $ES$ and $CS$ it is possible to describe the vulnerability of a given network. We consider a set of 17 different compl...

  16. 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

  17. 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 re

  18. Higher-order organization of complex networks.

    Science.gov (United States)

    Benson, Austin R; Gleich, David F; Leskovec, Jure

    2016-07-08

    Networks are a fundamental tool for understanding and modeling complex systems in physics, biology, neuroscience, engineering, and social science. Many networks are known to exhibit rich, lower-order connectivity patterns that can be captured at the level of individual nodes and edges. However, higher-order organization of complex networks--at the level of small network subgraphs--remains largely unknown. Here, we develop a generalized framework for clustering networks on the basis of higher-order connectivity patterns. This framework provides mathematical guarantees on the optimality of obtained clusters and scales to networks with billions of edges. The framework reveals higher-order organization in a number of networks, including information propagation units in neuronal networks and hub structure in transportation networks. Results show that networks exhibit rich higher-order organizational structures that are exposed by clustering based on higher-order connectivity patterns.

  19. Social Networks in Silicon Valley

    Institute of Scientific and Technical Information of China (English)

    Joseph Leu

    2006-01-01

    @@ Social network is a dominant, distinguishing characteristic of Silicon Valley. Because innovation entails coping with a high degree of uncertainty,such innovation is particularly dependent on networks.

  20. 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

  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. Foraging online social networks

    NARCIS (Netherlands)

    Koot, Gijs; Huis in ’t Veld, Mirjam; Hendricksen, Joost; Kaptein, Rianne; Vries, Arnout; Broek, van den Egon L.; Hengst, den M.; Israël, M.; Zeng, D.; Veenman, C.; Wang, A.

    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

  3. 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...

  4. Complex Networks and Socioeconomic Applications

    Science.gov (United States)

    Almendral, Juan A.; López, Luis; Mendes, Jose F.; Sanjuán, Miguel A. F.

    2003-04-01

    The study and characterization of complex systems is a fruitful research area nowadays. Special attention has been paid recently to complex networks, where graph and network analysis plays an important role since they reduce a given system to a simpler problem. Using a simple model for the information flow on social networks, we show that the traditional hierarchical topologies frequently used by companies and organizations, are poorly designed in terms of efficiency. Moreover, we prove that this type of structures are the result of the individual aim of monopolizing as much information as possible within the network. As the information is an appropriate measurement of centrality, we conclude that this kind of topology is so attractive for leaders because the global influence each actor has within the network is completely determined by the hierarchical level occupied. The effect on the efficiency caused by a change in a traditional hierarchical topology is also analyzed. In particular, by introducing the possibility of communication on the same level of the hierarchy.

  5. 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…

  6. 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…

  7. 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.

  8. Contagion on complex networks with persuasion

    CERN Document Server

    Huang, Wei-Min; Xu, Xin-Jian; Fu, Xinchu

    2016-01-01

    The threshold model has been widely adopted as a classic model for studying contagion processes on social networks. We consider asymmetric individual interactions in social networks and introduce a persuasion mechanism into the threshold model. Specifically, we study a combination of adoption and persuasion in cascading processes on complex networks. It is found that with the introduction of the persuasion mechanism, the system may become more vulnerable to global cascades, and the effects of persuasion tend to be more significant in heterogeneous networks than those in homogeneous networks: a comparison between heterogeneous and homogeneous networks shows that under weak persuasion, heterogeneous networks tend to be more robust against random shocks than homogeneous networks; whereas under strong persuasion, homogeneous networks are more stable. Finally, we study the effects of adoption and persuasion threshold heterogeneity on systemic stability. Though both heterogeneities give rise to global cascades, the...

  9. Social Networks as Marketing Tools

    National Research Council Canada - National Science Library

    NOZHA ERRAGCHA; RABIAA ROMDHANE

    2014-01-01

    The aims of this paper is to reinforce the literature on the digital social networks and their influences on the marketing Having presented and categorized the digital social, networks, we highlighted...

  10. Recent Advances in Complex Networks

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Dramatic advances in the field of complex networks have been witnessed in the past few years. This paper reviews some important results in this direction of rapidly evolving research, with emphasis on the relationship between the dynamics and the topology of complex networks. Basic quantities and typical examples of various complex networks are described. Robustness of connectivity and epidemic dynamics in complex networks are evaluated.

  11. Pleiotropy constrains the evolution of protein but not regulatory sequences in a transcription regulatory network influencing complex social behaviours

    Directory of Open Access Journals (Sweden)

    Daria eMolodtsova

    2014-12-01

    Full Text Available It is increasingly apparent that genes and networks that influence complex behaviour are evolutionary conserved, which is paradoxical considering that behaviour is labile over evolutionary timescales. How does adaptive change in behaviour arise if behaviour is controlled by conserved, pleiotropic, and likely evolutionary constrained genes? Pleiotropy and connectedness are known to constrain the general rate of protein evolution, prompting some to suggest that the evolution of complex traits, including behaviour, is fuelled by regulatory sequence evolution. However, we seldom have data on the strength of selection on mutations in coding and regulatory sequences, and this hinders our ability to study how pleiotropy influences coding and regulatory sequence evolution. Here we use population genomics to estimate the strength of selection on coding and regulatory mutations for a transcriptional regulatory network that influences complex behaviour of honey bees. We found that replacement mutations in highly connected transcription factors and target genes experience significantly stronger negative selection relative to weakly connected transcription factors and targets. Adaptively evolving proteins were significantly more likely to reside at the periphery of the regulatory network, while proteins with signs of negative selection were near the core of the network. Interestingly, connectedness and network structure had minimal influence on the strength of selection on putative regulatory sequences for both transcription factors and their targets. Our study indicates that adaptive evolution of complex behaviour can arise because of positive selection on protein-coding mutations in peripheral genes, and on regulatory sequence mutations in both transcription factors and their targets throughout the network.

  12. The Analysis of Social Networks

    OpenAIRE

    O’Malley, A James; Marsden, Peter V.

    2008-01-01

    Many questions about the social organization of medicine and health services involve interdependencies among social actors that may be depicted by networks of relationships. Social network studies have been pursued for some time in social science disciplines, where numerous descriptive methods for analyzing them have been proposed. More recently, interest in the analysis of social network data has grown among statisticians, who have developed more elaborate models and methods for fitting them...

  13. Articulation Points in Complex Networks

    CERN Document Server

    Tian, Liang; Shi, Da-Ning; Liu, Yang-Yu

    2016-01-01

    An articulation point in a network is a node whose removal disconnects the network. Those nodes play key roles in ensuring connectivity of many real-world networks, from infrastructure networks to protein interaction networks and terrorist communication networks. Despite their fundamental importance, a general framework of studying articulation points in complex networks is lacking. Here we develop analytical tools to study key issues pertinent to articulation points, e.g. the expected number of them and the network vulnerability against their removal, in an arbitrary complex network. We find that a greedy articulation point removal process provides us a novel perspective on the organizational principles of complex networks. Moreover, this process is associated with two fundamentally different types of percolation transitions with a rich phase diagram. Our results shed light on the design of more resilient infrastructure networks and the effective destruction of terrorist communication networks.

  14. Articulation points in complex networks

    Science.gov (United States)

    Tian, Liang; Bashan, Amir; Shi, Da-Ning; Liu, Yang-Yu

    2017-01-01

    An articulation point in a network is a node whose removal disconnects the network. Those nodes play key roles in ensuring connectivity of many real-world networks, from infrastructure networks to protein interaction networks and terrorist communication networks. Despite their fundamental importance, a general framework of studying articulation points in complex networks is lacking. Here we develop analytical tools to study key issues pertinent to articulation points, such as the expected number of them and the network vulnerability against their removal, in an arbitrary complex network. We find that a greedy articulation point removal process provides us a different perspective on the organizational principles of complex networks. Moreover, this process results in a rich phase diagram with two fundamentally different types of percolation transitions. Our results shed light on the design of more resilient infrastructure networks and the effective destruction of terrorist communication networks.

  15. Articulation points in complex networks

    Science.gov (United States)

    Tian, Liang; Bashan, Amir; Shi, Da-Ning; Liu, Yang-Yu

    2017-01-01

    An articulation point in a network is a node whose removal disconnects the network. Those nodes play key roles in ensuring connectivity of many real-world networks, from infrastructure networks to protein interaction networks and terrorist communication networks. Despite their fundamental importance, a general framework of studying articulation points in complex networks is lacking. Here we develop analytical tools to study key issues pertinent to articulation points, such as the expected number of them and the network vulnerability against their removal, in an arbitrary complex network. We find that a greedy articulation point removal process provides us a different perspective on the organizational principles of complex networks. Moreover, this process results in a rich phase diagram with two fundamentally different types of percolation transitions. Our results shed light on the design of more resilient infrastructure networks and the effective destruction of terrorist communication networks. PMID:28139697

  16. Correlation dimension of complex networks

    CERN Document Server

    Lacasa, Lucas

    2012-01-01

    We propose a new measure to characterize the dimension of complex networks based on the ergodic theory of dynamical systems. This measure is derived from the correlation sum of a trajectory generated by a random walker navigating the network, and extends the classical Grassberger-Procaccia algorithm to the context of complex networks. The method is validated with reliable results for both synthetic networks and real-world networks such as the world air-transportation network or urban networks, and provides a computationally fast way for estimating the dimensionality of networks which only relies on the local information provided by the walkers.

  17. The Social Networks of Innovation

    DEFF Research Database (Denmark)

    Björk, Jennie; Bergenholtz, Carsten; Magnusson, Mats

    It is a well-known fact in the innovation management literature that social network structures both constrain and facilitate ideation activities within firm boundaries. Still, recent research shows how the impact of social network structures varies across different contexts, depending e......) the characteristics of individuals involved in the given ideation process and 3) the social network activities of these individuals. The dependent variables are based on the idea level. Our research objective is two-fold: We explore how different kinds of social networks develop around varying idea categories...... and explain how particular social network structures facilitate some ideas to fare more successfully than others....

  18. The Social Networks of Innovation

    DEFF Research Database (Denmark)

    Björk, Jennie; Bergenholtz, Carsten; Magnusson, Mats

    It is a well-known fact in the innovation management literature that social network structures both constrain and facilitate ideation activities within firm boundaries. Still, recent research shows how the impact of social network structures varies across different contexts, depending e......) the characteristics of individuals involved in the given ideation process and 3) the social network activities of these individuals. The dependent variables are based on the idea level. Our research objective is two-fold: We explore how different kinds of social networks develop around varying idea categories...... and explain how particular social network structures facilitate some ideas to fare more successfully than others....

  19. Note on the Complex Networks and Epidemiology Part I: Complex Networks

    CERN Document Server

    Kim, James

    2013-01-01

    Complex networks describe a wide range of systems in nature and society. Frequently cited examples include Internet, WWW, a network of chemicals linked by chemical reactions, social relationship networks, citation networks, etc. The research of complex networks has attracted many scientists' attention. Physicists have shown that these networks exhibit some surprising characters, such as high clustering coefficient, small diameter, and the absence of the thresholds of percolation. Scientists in mathematical epidemiology discovered that the threshold of infectious disease disappears on contact networks that following Scale-Free distribution. Researchers in economics and public health also find that the imitation behavior could lead to cluster phenomena of vaccination and un-vaccination. In this note, we will review the basic concepts of complex networks; Basic epidemic models; the development of complex networks and epidemiology.

  20. SYNCHRONIZATION IN COMPLEX DYNAMICAL NETWORKS

    Institute of Scientific and Technical Information of China (English)

    WANG Xiaofan; CHEN Guanrong

    2003-01-01

    In the past few years, the discovery of small-world and scale-free properties of many natural and artificial complex networks has stimulated increasing interest in further studying the underlying organizing principles of various complex networks. This has led to significant advances in understanding the relationship between the topology and the dynamics of such complex networks. This paper reviews some recent research works on the synchronization phenomenon in various dynamical networks with small-world and scalefree connections.

  1. 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.

  2. Spreading dynamics in complex networks

    Science.gov (United States)

    Pei, Sen; Makse, Hernán A.

    2013-12-01

    Searching for influential spreaders in complex networks is an issue of great significance for applications across various domains, ranging from epidemic control, innovation diffusion, viral marketing, and social movement to idea propagation. In this paper, we first display some of the most important theoretical models that describe spreading processes, and then discuss the problem of locating both the individual and multiple influential spreaders respectively. Recent approaches in these two topics are presented. For the identification of privileged single spreaders, we summarize several widely used centralities, such as degree, betweenness centrality, PageRank, k-shell, etc. We investigate the empirical diffusion data in a large scale online social community—LiveJournal. With this extensive dataset, we find that various measures can convey very distinct information of nodes. Of all the users in the LiveJournal social network, only a small fraction of them are involved in spreading. For the spreading processes in LiveJournal, while degree can locate nodes participating in information diffusion with higher probability, k-shell is more effective in finding nodes with a large influence. Our results should provide useful information for designing efficient spreading strategies in reality.

  3. Controlling complex networks with conformity behavior

    Science.gov (United States)

    Wang, Xu-Wen; Nie, Sen; Wang, Wen-Xu; Wang, Bing-Hong

    2015-09-01

    Controlling complex networks accompanied by common conformity behavior is a fundamental problem in social and physical science. Conformity behavior that individuals tend to follow the majority in their neighborhood is common in human society and animal communities. Despite recent progress in understanding controllability of complex networks, the existent controllability theories cannot be directly applied to networks associated with conformity. Here we propose a simple model to incorporate conformity-based decision making into the evolution of a network system, which allows us to employ the exact controllability theory to explore the controllability of such systems. We offer rigorous theoretical results of controllability for representative regular networks. We also explore real networks in different fields and some typical model networks, finding some interesting results that are different from the predictions of structural and exact controllability theory in the absence of conformity. We finally present an example of steering a real social network to some target states to further validate our controllability theory and tools. Our work offers a more realistic understanding of network controllability with conformity behavior and can have potential applications in networked evolutionary games, opinion dynamics and many other complex networked systems.

  4. Towards an Information Theory of Complex Networks

    CERN Document Server

    Dehmer, Matthias; Mehler, Alexander

    2011-01-01

    For over a decade, complex networks have steadily grown as an important tool across a broad array of academic disciplines, with applications ranging from physics to social media. A tightly organized collection of carefully-selected papers on the subject, Towards an Information Theory of Complex Networks: Statistical Methods and Applications presents theoretical and practical results about information-theoretic and statistical models of complex networks in the natural sciences and humanities. The book's major goal is to advocate and promote a combination of graph-theoretic, information-theoreti

  5. 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...

  6. Structural complexity of quantum networks

    Energy Technology Data Exchange (ETDEWEB)

    Siomau, Michael [Physics Department, Jazan University, P.O.Box 114, 45142 Jazan (Saudi Arabia); Network Dynamics, Max Planck Institute for Dynamics and Self-Organization (MPIDS), 37077 Göttingen (Germany)

    2016-06-10

    Quantum network is a set of nodes connected with channels, through which the nodes communicate photons and classical information. Classical structural complexity of a quantum network may be defined through its physical structure, i.e. mutual position of nodes and channels connecting them. We show here that the classical structural complexity of a quantum network does not restrict the structural complexity of entanglement graphs, which may be created in the quantum network with local operations and classical communication. We show, in particular, that 1D quantum network can simulate both simple entanglement graphs such as lattices and random graphs and complex small-world graphs.

  7. Applications of Social Network Analysis

    Science.gov (United States)

    Thilagam, P. Santhi

    A social network [2] is a description of the social structure between actors, mostly persons, groups or organizations. It indicates the ways in which they are connected with each other by some relationship such as friendship, kinship, finance exchange etc. In a nutshell, when the person uses already known/unknown people to create new contacts, it forms social networking. The social network is not a new concept rather it can be formed when similar people interact with each other directly or indirectly to perform particular task. Examples of social networks include a friendship networks, collaboration networks, co-authorship networks, and co-employees networks which depict the direct interaction among the people. There are also other forms of social networks, such as entertainment networks, business Networks, citation networks, and hyperlink networks, in which interaction among the people is indirect. Generally, social networks operate on many levels, from families up to the level of nations and assists in improving interactive knowledge sharing, interoperability and collaboration.

  8. Collaboration in Social Networks

    CERN Document Server

    Dall'Asta, Luca; Pin, Paolo

    2011-01-01

    The very notion of social network implies that linked individuals interact repeatedly with each other. This allows them not only to learn successful strategies and adapt to them, but also to condition their own behavior on the behavior of others, in a strategic forward looking manner. Game theory of repeated games shows that these circumstances are conducive to the emergence of collaboration in simple games of two players. We investigate the extension of this concept to the case where players are engaged in a local contribution game and show that rationality and credibility of threats identify a class of Nash equilibria -- that we call "collaborative equilibria" -- that have a precise interpretation in terms of sub-graphs of the social network. For large network games, the number of such equilibria is exponentially large in the number of players. When incentives to defect are small, equilibria are supported by local structures whereas when incentives exceed a threshold they acquire a non-local nature, which r...

  9. Synchronization in Triangled Complex Networks

    Institute of Scientific and Technical Information of China (English)

    LU Xin-Biao; LI Xiang; WANG Xiao-Fan

    2006-01-01

    Using a tunable clustering coefficient model withoutchanging the degree distribution, we investigate the effect of clustering coefficient on synchronization of networks with both unweighted and weighted couplings. For several typical categories of complex networks, the more triangles are in the networks, the worse the synchronizability of the networks is.

  10. 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

  11. Complex networks analysis of language complexity

    CERN Document Server

    Amancio, Diego R; Oliveira, Osvaldo N; Costa, Luciano da F; 10.1209/0295-5075/100/58002

    2013-01-01

    Methods from statistical physics, such as those involving complex networks, have been increasingly used in quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification in co-occurrence networks and found that topological regularity correlated negatively with textual complexity. Furthermore, in less complex texts the distance between concepts, represented as nodes, tended to decrease. The complex networks metrics were treated with multivariate pattern recognition techniques, which allowed us to distinguish between original texts and their simplified versions. For each original text, two simplified versions were generated manually with increasing number of simplification operations. As expected, distinction was easier for the strongly simplified versions, where the most relevant metrics were node strength, shortest paths and diversity. Also, the discrimination of complex texts was improved with higher hierarchical network metrics, thus point...

  12. Multiagent task allocation in social networks

    NARCIS (Netherlands)

    De Weerdt, M.M.; Zhang, Y.; Klos, T.

    2011-01-01

    This paper proposes a new variant of the task allocation problem, where the agents are connected in a social network and tasks arrive at the agents distributed over the network. We show that the complexity of this problem remains NP-complete. Moreover, it is not approximable within some factor. In c

  13. Distributed Task Allocation in Social Networks

    NARCIS (Netherlands)

    De Weerdt, M.M.; Zhang, Y.; Klos, T.

    2007-01-01

    This paper proposes a new variant of the task allocation problem, where the agents are connected in a social network and tasks arrive at the agents distributed over the network. We show that the complexity of this problem remains NPhard. Moreover, it is not approximable within some factor. We develo

  14. Multiagent task allocation in social networks

    NARCIS (Netherlands)

    M.M. de Weerdt (Mathijs); Y. Zhang (Yingqian); T.B. Klos (Tomas)

    2011-01-01

    textabstractThis paper proposes a new variant of the task allocation problem, where the agents are connected in a social network and tasks arrive at the agents distributed over the network. We show that the complexity of this problem remains NP-complete. Moreover, it is not approximable within some

  15. Social Network Analysis Based on Network Motifs

    OpenAIRE

    2014-01-01

    Based on the community structure characteristics, theory, and methods of frequent subgraph mining, network motifs findings are firstly introduced into social network analysis; the tendentiousness evaluation function and the importance evaluation function are proposed for effectiveness assessment. Compared with the traditional way based on nodes centrality degree, the new approach can be used to analyze the properties of social network more fully and judge the roles of the nodes effectively. I...

  16. 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…

  17. 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…

  18. 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

  19. 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

  20. 7th Workshop on Complex Networks

    CERN Document Server

    Gonçalves, Bruno; Menezes, Ronaldo; Sinatra, Roberta

    2016-01-01

    The last decades have seen the emergence of Complex Networks as the language with which a wide range of complex phenomena in fields as diverse as Physics, Computer Science, and Medicine (to name just a few) can be properly described and understood. This book provides a view of the state of the art in this dynamic field and covers topics ranging from network controllability, social structure, online behavior, recommendation systems, and network structure. This book includes the peer-reviewed list of works presented at the 7th Workshop on Complex Networks CompleNet 2016 which was hosted by the Université de Bourgogne, France, from March 23-25, 2016. The 28 carefully reviewed and selected contributions in this book address many topics related to complex networks and have been organized in seven major groups: (1) Theory of Complex Networks, (2) Multilayer networks, (3) Controllability of networks, (4) Algorithms for networks, (5) Community detection, (6) Dynamics and spreading phenomena on networks, (7) Applicat...

  1. Graph distance for complex networks

    Science.gov (United States)

    Shimada, Yutaka; Hirata, Yoshito; Ikeguchi, Tohru; Aihara, Kazuyuki

    2016-10-01

    Networks are widely used as a tool for describing diverse real complex systems and have been successfully applied to many fields. The distance between networks is one of the most fundamental concepts for properly classifying real networks, detecting temporal changes in network structures, and effectively predicting their temporal evolution. However, this distance has rarely been discussed in the theory of complex networks. Here, we propose a graph distance between networks based on a Laplacian matrix that reflects the structural and dynamical properties of networked dynamical systems. Our results indicate that the Laplacian-based graph distance effectively quantifies the structural difference between complex networks. We further show that our approach successfully elucidates the temporal properties underlying temporal networks observed in the context of face-to-face human interactions.

  2. Statistical mechanics of complex networks

    CERN Document Server

    Rubi, Miguel; Diaz-Guilera, Albert

    2003-01-01

    Networks can provide a useful model and graphic image useful for the description of a wide variety of web-like structures in the physical and man-made realms, e.g. protein networks, food webs and the Internet. The contributions gathered in the present volume provide both an introduction to, and an overview of, the multifaceted phenomenology of complex networks. Statistical Mechanics of Complex Networks also provides a state-of-the-art picture of current theoretical methods and approaches.

  3. Three Types of Network Complexity Pyramid

    Institute of Scientific and Technical Information of China (English)

    FANG; Jin-qing; LI; Yong; LIU; Qiang

    2012-01-01

    <正>Exploring the complexity and diversity of complex networks have been very challenging issues in network science and engineering. Among them exploring the network complexity pyramids (NCP) are one of important expressions in network complexity. So far as we have proposed the three types of the network complexity pyramid (NCP). The first type of NCP is the network model complexity pyramid with

  4. Epidemic dynamics on complex networks

    Institute of Scientific and Technical Information of China (English)

    ZHOU Tao; FU Zhongqian; WANG Binghong

    2006-01-01

    Recently, motivated by the pioneer work in revealing the small-world effect and scale-free property of various real-life networks, many scientists devote themselves to studying complex networks. One of the ultimate goals is to understand how the topological structures affect the dynamics upon networks. In this paper, we give a brief review on the studies of epidemic dynamics on complex networks, including the description of classical epidemic models, the epidemic spread on small-world and scale-free networks, and network immunization. Finally, perspectives and some interesting problems are proposed.

  5. Complex Dynamics in Communication Networks

    CERN Document Server

    Kocarev, Ljupco

    2005-01-01

    Computer and communication networks are among society's most important infrastructures. The internet, in particular, is a giant global network of networks without central control or administration. It is a paradigm of a complex system, where complexity may arise from different sources: topological structure, network evolution, connection and node diversity, or dynamical evolution. The present volume is the first book entirely devoted to the new and emerging field of nonlinear dynamics of TCP/IP networks. It addresses both scientists and engineers working in the general field of communication networks.

  6. Fundamental structures of dynamic social networks

    DEFF Research Database (Denmark)

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

    2016-01-01

    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...... a pattern of recurring meetings across weeks and months, each with varying degrees of regularity. Taken together, these findings provide a powerful simplification of the social network, where cores represent fundamental structures expressed with strong temporal and spatial regularity. Using this framework......, we explore the complex interplay between social and geospatial behavior, documenting how the formation of cores is preceded by coordination behavior in the communication networks and demonstrating that social behavior can be predicted with high precision....

  7. 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.

  8. 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.

  9. Social Networks in Silicon Valley

    Institute of Scientific and Technical Information of China (English)

    Joseph; Leu

    2006-01-01

      Social network is a dominant, distinguishing characteristic of Silicon Valley. Because innovation entails coping with a high degree of uncertainty,such innovation is particularly dependent on networks.……

  10. 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.

  11. 8th Conference on Complex Networks

    CERN Document Server

    Menezes, Ronaldo; Sinatra, Roberta; Zlatic, Vinko

    2017-01-01

    This book collects the works presented at the 8th International Conference on Complex Networks (CompleNet) 2017 in Dubrovnik, Croatia, on March 21-24, 2017. CompleNet aims at bringing together researchers and practitioners working in areas related to complex networks. The past two decades has witnessed an exponential increase in the number of publications within this field. From biological systems to computer science, from economic to social systems, complex networks are becoming pervasive in many fields of science. It is this interdisciplinary nature of complex networks that CompleNet aims at addressing. The last decades have seen the emergence of complex networks as the language with which a wide range of complex phenomena in fields as diverse as physics, computer science, and medicine (to name a few) can be properly described and understood. This book provides a view of the state-of-the-art in this dynamic field and covers topics such as network controllability, social structure, online behavior, recommend...

  12. Fundamental structures of dynamic social networks.

    Science.gov (United States)

    Sekara, Vedran; Stopczynski, Arkadiusz; Lehmann, Sune

    2016-09-06

    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 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 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 unnecessary. Starting from 5-min time slices, we uncover dynamic social structures expressed on multiple timescales. On the hourly timescale, we find that gatherings are fluid, with members coming and going, but organized via a stable core of individuals. Each core represents a social context. Cores exhibit a pattern of recurring meetings across weeks and months, each with varying degrees of regularity. Taken together, these findings provide a powerful simplification of the social network, where cores represent fundamental structures expressed with strong temporal and spatial regularity. Using this framework, we explore the complex interplay between social and geospatial behavior, documenting how the formation of cores is preceded by coordination behavior in the communication networks and demonstrating that social behavior can be predicted with high precision.

  13. The price of complexity in financial networks.

    Science.gov (United States)

    Battiston, Stefano; Caldarelli, Guido; May, Robert M; Roukny, Tarik; Stiglitz, Joseph E

    2016-09-06

    Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises.

  14. The price of complexity in financial networks

    Science.gov (United States)

    Battiston, Stefano; Caldarelli, Guido; May, Robert M.; Roukny, Tarik; Stiglitz, Joseph E.

    2016-09-01

    Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises.

  15. The price of complexity in financial networks

    Science.gov (United States)

    May, Robert M.; Roukny, Tarik; Stiglitz, Joseph E.

    2016-01-01

    Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises. PMID:27555583

  16. Effective Augmentation of Complex Networks

    Science.gov (United States)

    Wang, Jinjian; Yu, Xinghuo; Stone, Lewi

    2016-05-01

    Networks science plays an enormous role in many aspects of modern society from distributing electrical power across nations to spreading information and social networking amongst global populations. While modern networks constantly change in size, few studies have sought methods for the difficult task of optimising this growth. Here we study theoretical requirements for augmenting networks by adding source or sink nodes, without requiring additional driver-nodes to accommodate the change i.e., conserving structural controllability. Our “effective augmentation” algorithm takes advantage of clusters intrinsic to the network topology, and permits rapidly and efficient augmentation of a large number of nodes in one time-step. “Effective augmentation” is shown to work successfully on a wide range of model and real networks. The method has numerous applications (e.g. study of biological, social, power and technological networks) and potentially of significant practical and economic value.

  17. Epidemic Diffusion on Complex Networks

    Institute of Scientific and Technical Information of China (English)

    WU Xiao-Yan; LIU Zong-Hua

    2007-01-01

    Boyh diffusion and epidemic are well studied in the stochastic systems and complex networks,respetively.Here we combine these two fields and study epidemic diffusion in complex networks.Instead of studying the threshold of infection,which was focused on in previous works,we focus on the diffusion.behaviour.We find that the epidemic diffusion in a complex network is an anomalous superdiffusion with varyingg diffusion exponext γand that γ is influenced seriously by the network structure,such as the clustering coefficient and the degree distribution.Numerical simulations have confirmed the theoretical predictions.

  18. Multifractal analysis of complex networks

    Institute of Scientific and Technical Information of China (English)

    Wang Dan-Ling; Yu Zu-Guo; Anh V

    2012-01-01

    Complex networks have recently attracted much attention in diverse areas of science and technology.Many networks such as the WWW and biological networks are known to display spatial heterogeneity which can be characterized by their fractal dimensions.Multifractal analysis is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns.In this paper,we introduce a new box-covering algorithm for muttifractal analysis of complex networks.This algorithm is used to calculate the generalized fractal dimensions Dq of some theoretical networks,namely scale-free networks,small world networks,and random networks,and one kind of real network,namely protein-protein interaction networks of different species.Our numerical results indicate the existence of multifractality in scale-free networks and protein-protein interaction networks,while the multifractal behavior is not clear-cut for small world networks and random networks.The possible variation of Dq due to changes in the parameters of the theoretical network models is also discussed.

  19. Complex Dynamics in Information Sharing Networks

    Science.gov (United States)

    Cronin, Bruce

    This study examines the roll-out of an electronic knowledge base in a medium-sized professional services firm over a six year period. The efficiency of such implementation is a key business problem in IT systems of this type. Data from usage logs provides the basis for analysis of the dynamic evolution of social networks around the depository during this time. The adoption pattern follows an "s-curve" and usage exhibits something of a power law distribution, both attributable to network effects, and network position is associated with organisational performance on a number of indicators. But periodicity in usage is evident and the usage distribution displays an exponential cut-off. Further analysis provides some evidence of mathematical complexity in the periodicity. Some implications of complex patterns in social network data for research and management are discussed. The study provides a case study demonstrating the utility of the broad methodological approach.

  20. A Sensemaking Approach to Visual Analytics of Attribute-Rich Social Networks

    Science.gov (United States)

    Gou, Liang

    2012-01-01

    Social networks have become more complex, in particular considering the fact that elements in social networks are not only abstract topological nodes and links, but contain rich social attributes and reflecting diverse social relationships. For example, in a co-authorship social network in a scientific community, nodes in the social network, which…

  1. A Sensemaking Approach to Visual Analytics of Attribute-Rich Social Networks

    Science.gov (United States)

    Gou, Liang

    2012-01-01

    Social networks have become more complex, in particular considering the fact that elements in social networks are not only abstract topological nodes and links, but contain rich social attributes and reflecting diverse social relationships. For example, in a co-authorship social network in a scientific community, nodes in the social network, which…

  2. Synchronization in uncertain complex networks

    Science.gov (United States)

    Chen, Maoyin; Zhou, Donghua

    2006-03-01

    We consider the problem of synchronization in uncertain generic complex networks. For generic complex networks with unknown dynamics of nodes and unknown coupling functions including uniform and nonuniform inner couplings, some simple linear feedback controllers with updated strengths are designed using the well-known LaSalle invariance principle. The state of an uncertain generic complex network can synchronize an arbitrary assigned state of an isolated node of the network. The famous Lorenz system is stimulated as the nodes of the complex networks with different topologies. We found that the star coupled and scale-free networks with nonuniform inner couplings can be in the state of synchronization if only a fraction of nodes are controlled.

  3. 6th Workshop on Complex Networks

    CERN Document Server

    Simini, Filippo; Uzzo, Stephen; Wang, Dashun

    2015-01-01

    Elucidating the spatial and temporal dynamics of how things connect has become one of the most important areas of research in the 21st century. Network science now pervades nearly every science domain, resulting in new discoveries in a host of dynamic social and natural systems, including: how neurons connect and communicate in the brain, how information percolates within and among social networks, the evolution of science research through co-authorship networks, the spread of epidemics, and many other complex phenomena. Over the past decade, advances in computational power have put the tools of network analysis in the hands of increasing numbers of scientists, enabling more explorations of our world than ever before possible. Information science, social sciences, systems biology, ecosystems ecology, neuroscience and physics all benefit from this movement, which combines graph theory with data sciences to develop and validate theories about the world around us. This book brings together cutting-edge research ...

  4. 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.

  5. Statistically validated networks in bipartite complex systems.

    Directory of Open Access Journals (Sweden)

    Michele Tumminello

    Full Text Available Many complex systems present an intrinsic bipartite structure where elements of one set link to elements of the second set. In these complex systems, such as the system of actors and movies, elements of one set are qualitatively different than elements of the other set. The properties of these complex systems are typically investigated by constructing and analyzing a projected network on one of the two sets (for example the actor network or the movie network. Complex systems are often very heterogeneous in the number of relationships that the elements of one set establish with the elements of the other set, and this heterogeneity makes it very difficult to discriminate links of the projected network that are just reflecting system's heterogeneity from links relevant to unveil the properties of the system. Here we introduce an unsupervised method to statistically validate each link of a projected network against a null hypothesis that takes into account system heterogeneity. We apply the method to a biological, an economic and a social complex system. The method we propose is able to detect network structures which are very informative about the organization and specialization of the investigated systems, and identifies those relationships between elements of the projected network that cannot be explained simply by system heterogeneity. We also show that our method applies to bipartite systems in which different relationships might have different qualitative nature, generating statistically validated networks in which such difference is preserved.

  6. Controlling edge dynamics in complex networks

    CERN Document Server

    Nepusz, Tamás

    2011-01-01

    The interaction of distinct units in physical, social, biological and technological systems naturally gives rise to complex network structures. Networks have constantly been in the focus of research for the last decade, with considerable advances in the description of their structural and dynamical properties. However, much less effort has been devoted to studying the controllability of the dynamics taking place on them. Here we introduce and evaluate a dynamical process defined on the edges of a network, and demonstrate that the controllability properties of this process significantly differ from simple nodal dynamics. Evaluation of real-world networks indicates that most of them are more controllable than their randomized counterparts. We also find that transcriptional regulatory networks are particularly easy to control. Analytic calculations show that networks with scale-free degree distributions have better controllability properties than uncorrelated networks, and positively correlated in- and out-degre...

  7. Controlling edge dynamics in complex networks

    OpenAIRE

    Nepusz, Tamás; Vicsek, Tamás

    2012-01-01

    The interaction of distinct units in physical, social, biological and technological systems naturally gives rise to complex network structures. Networks have constantly been in the focus of research for the last decade, with considerable advances in the description of their structural and dynamical properties. However, much less effort has been devoted to studying the controllability of the dynamics taking place on them. Here we introduce and evaluate a dynamical process defined on the edges ...

  8. 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…

  9. 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…

  10. 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...

  11. 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

  12. Combinatorial Laplacian and entropy of simplicial complexes associated with complex networks

    Science.gov (United States)

    Maletić, S.; Rajković, M.

    2012-09-01

    Simplicial complexes represent useful and accurate models of complex networks and complex systems in general. We explore the properties of spectra of combinatorial Laplacian operator of simplicial complexes and show its relationship with connectivity properties of the Q-vector and with connectivities of cliques in the simplicial clique complex. We demonstrate the need for higher order analysis in complex networks and compare the results with ordinary graph spectra. Methods and results are obtained using social network of the Zachary karate club.

  13. Bridges in Complex Networks

    CERN Document Server

    Wu, Ang-Kun; Liu, Yang-Yu

    2016-01-01

    A bridge in a graph is an edge whose removal disconnects the graph and increases the number of connected components. We calculate the fraction of bridges in a wide range of real-world networks and their randomized counterparts. We find that real networks typically have more bridges than their completely randomized counterparts, but very similar fraction of bridges as their degree-preserving randomizations. We define a new edge centrality measure, called bridgeness, to differentiate the importance of a bridge in damaging a network. We find that certain real networks have very large average and variance of bridgeness compared to their degree-preserving randomizations and other real networks. Finally, we offer an analytical framework to calculate the bridge fraction and average bridgeness for uncorrelated random networks with arbitrary degree distributions.

  14. 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...... sources. These results point out the roles non-market arrangements, such as social networks, can play in mitigating market inefficiencies in poor rural markets....... 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...

  15. Signed Networks in Social Media

    CERN Document Server

    Leskovec, Jure; 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 classical theory of structural balance tends to capture certain common patterns of interaction, but that it is also at odds with some of the fundamental phenomena we observe --- particularly related to the evolving, directed nature of these on-line networks. We then develop an alternate theory of status that better explains the observed edge signs and provides insights into the underlying social mechanisms. Our work provides one of the first large-scale evaluations of theories of signed networks using on-line datasets, as ...

  16. Line graphs as social networks

    CERN Document Server

    Krawczyk, Malgorzata; Mańka-Krasoń, Anna; Kułakowski, Krzysztof

    2010-01-01

    The line graphs are clustered and assortative. They share these topological features with some social networks. We argue that this similarity reveals the cliquey character of the social networks. In the model proposed here, a social network is the line graph of an initial network of families, communities, interest groups, school classes and small companies. These groups play the role of nodes, and individuals are represented by links between these nodes. The picture is supported by the data on the LiveJournal network of about 8 x 10^6 people. In particular, sharp maxima of the observed data of the degree dependence of the clustering coefficient C(k) are associated with cliques in the social network.

  17. Topological structural classes of complex networks

    Science.gov (United States)

    Estrada, Ernesto

    2007-01-01

    We use theoretical principles to study how complex networks are topologically organized at large scale. Using spectral graph theory we predict the existence of four different topological structural classes of networks. These classes correspond, respectively, to highly homogenous networks lacking structural bottlenecks, networks organized into highly interconnected modules with low inter-community connectivity, networks with a highly connected central core surrounded by a sparser periphery, and networks displaying a combination of highly connected groups (quasicliques) and groups of nodes partitioned into disjoint subsets (quasibipartites). Here we show by means of the spectral scaling method that these classes really exist in real-world ecological, biological, informational, technological, and social networks. We show that neither of three network growth mechanisms—random with uniform distribution, preferential attachment, and random with the same degree sequence as real network—is able to reproduce the four structural classes of complex networks. These models reproduce two of the network classes as a function of the average degree but completely fail in reproducing the other two classes of networks.

  18. Forman curvature for complex networks

    Science.gov (United States)

    Sreejith, R. P.; Mohanraj, Karthikeyan; Jost, Jürgen; Saucan, Emil; Samal, Areejit

    2016-06-01

    We adapt Forman’s discretization of Ricci curvature to the case of undirected networks, both weighted and unweighted, and investigate the measure in a variety of model and real-world networks. We find that most nodes and edges in model and real networks have a negative curvature. Furthermore, the distribution of Forman curvature of nodes and edges is narrow in random and small-world networks, while the distribution is broad in scale-free and real-world networks. In most networks, Forman curvature is found to display significant negative correlation with degree and centrality measures. However, Forman curvature is uncorrelated with clustering coefficient in most networks. Importantly, we find that both model and real networks are vulnerable to targeted deletion of nodes with highly negative Forman curvature. Our results suggest that Forman curvature can be employed to gain novel insights on the organization of complex networks.

  19. Parallel Graph Partitioning for Complex Networks

    CERN Document Server

    Meyerhenke, Henning; Schulz, Christian

    2014-01-01

    Processing large complex networks like social networks or web graphs has recently attracted considerable interest. In order to do this in parallel, we need to partition them into pieces of about equal size. Unfortunately, previous parallel graph partitioners originally developed for more regular mesh-like networks do not work well for these networks. This paper addresses this problem by parallelizing and adapting the label propagation technique originally developed for graph clustering. By introducing size constraints, label propagation becomes applicable for both the coarsening and the refinement phase of multilevel graph partitioning. We obtain very high quality by applying a highly parallel evolutionary algorithm to the coarsened graph. The resulting system is both more scalable and achieves higher quality than state-of-the-art systems like ParMetis or PT-Scotch. For large complex networks the performance differences are very big. For example, our algorithm can partition a web graph with 3.3 billion edges ...

  20. ELASTICITY:Topological characterization of robustness in complex networks

    NARCIS (Netherlands)

    Sydney, A.; Scoglio, C.; Schumm, P.; Kooij, R.E.

    2008-01-01

    Just as a herd of animals relies on its robust social structure to survive in the wild, similarly robustness is a crucial characteristic for the survival of a complex network under attack. The capacity to measure robustness in complex networks defines a network's survivability in the advent of class

  1. ELASTICITY:Topological characterization of robustness in complex networks

    NARCIS (Netherlands)

    Sydney, A.; Scoglio, C.; Schumm, P.; Kooij, R.E.

    2008-01-01

    Just as a herd of animals relies on its robust social structure to survive in the wild, similarly robustness is a crucial characteristic for the survival of a complex network under attack. The capacity to measure robustness in complex networks defines a network's survivability in the advent of class

  2. SOCIAL NETWORKS AND INTERPERSONAL COMMUNICATION

    OpenAIRE

    Veronica GHEORGHIȚĂ; Alexandrina PĂDUREȚU

    2014-01-01

    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 t...

  3. The Kuramoto model in complex networks

    CERN Document Server

    Rodrigues, Francisco A; Ji, Peng; Kurths, Jürgen

    2016-01-01

    Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from social and physical to biological and technological systems. The most successful approach to describe how coherent behavior emerges in these complex systems is given by the paradigmatic Kuramoto model. This model has been traditionally studied in complete graphs. However, besides being intrinsically dynamical, complex systems present very heterogeneous structure, which can be represented as complex networks. This report is dedicated to review main contributions in the field of synchronization in networks of Kuramoto oscillators. In particular, we provide an overview of the impact of network patterns on the local and global dynamics of coupled phase oscillators. We cover many relevant topics, which encompass a description of the most used analytical approaches and the analysis of several numerical results. Furthermore, we discuss recent developments on variations of the Kuramoto model in net...

  4. The regulation of social recognition, social communication and aggression: vasopressin in the social behavior neural network.

    Science.gov (United States)

    Albers, H Elliott

    2012-03-01

    Neuropeptides in the arginine vasotocin/arginine vasopressin (AVT/AVP) family play a major role in the regulation of social behavior by their actions in the brain. In mammals, AVP is found within a circuit of recriprocally connected limbic structures that form the social behavior neural network. This review examines the role played by AVP within this network in controlling social processes that are critical for the formation and maintenance of social relationships: social recognition, social communication and aggression. Studies in a number of mammalian species indicate that AVP and AVP V1a receptors are ideally suited to regulate the expression of social processes because of their plasticity in response to factors that influence social behavior. The pattern of AVP innervation and V1a receptors across the social behavior neural network may determine the potential range and intensity of social responses that individuals display in different social situations. Although fundamental information on how social behavior is wired in the brain is still lacking, it is clear that different social behaviors can be influenced by the actions of AVP in the same region of the network and that AVP can act within multiple regions of this network to regulate the expression of individual social behaviors. The existing data suggest that AVP can influence social behavior by modulating the interpretation of sensory information, by influencing decision making and by triggering complex motor outputs. This article is part of a Special Issue entitled Oxytocin, Vasopressin, and Social Behavior. Copyright © 2011 Elsevier Inc. All rights reserved.

  5. 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?

  6. 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.

  7. 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.

  8. Introduction to Social Network Analysis

    Science.gov (United States)

    Zaphiris, Panayiotis; Ang, Chee Siang

    Social Network analysis focuses on patterns of relations between and among people, organizations, states, etc. It aims to describe networks of relations as fully as possible, identify prominent patterns in such networks, trace the flow of information through them, and discover what effects these relations and networks have on people and organizations. Social network analysis offers a very promising potential for analyzing human-human interactions in online communities (discussion boards, newsgroups, virtual organizations). This Tutorial provides an overview of this analytic technique and demonstrates how it can be used in Human Computer Interaction (HCI) research and practice, focusing especially on Computer Mediated Communication (CMC). This topic acquires particular importance these days, with the increasing popularity of social networking websites (e.g., youtube, myspace, MMORPGs etc.) and the research interest in studying them.

  9. 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...

  10. Line graphs as social networks

    Science.gov (United States)

    Krawczyk, M. J.; Muchnik, L.; Mańka-Krasoń, A.; Kułakowski, K.

    2011-07-01

    It was demonstrated recently that the line graphs are clustered and assortative. These topological features are known to characterize some social networks [M.E.J. Newman, Y. Park, Why social networks are different from other types of networks, Phys. Rev. E 68 (2003) 036122]; it was argued that this similarity reveals their cliquey character. In the model proposed here, a social network is the line graph of an initial network of families, communities, interest groups, school classes and small companies. These groups play the role of nodes, and individuals are represented by links between these nodes. The picture is supported by the data on the LiveJournal network of about 8×10 6 people.

  11. Complex networks: Dynamics and security

    Indian Academy of Sciences (India)

    Ying-Cheng Lai; Adilson Motter; Takashi Nishikawa; Kwangho Park; Liang Zhao

    2005-04-01

    This paper presents a perspective in the study of complex networks by focusing on how dynamics may affect network security under attacks. In particular, we review two related problems: attack-induced cascading breakdown and range-based attacks on links. A cascade in a network means the failure of a substantial fraction of the entire network in a cascading manner, which can be induced by the failure of or attacks on only a few nodes. These have been reported for the internet and for the power grid (e.g., the August 10, 1996 failure of the western United States power grid). We study a mechanism for cascades in complex networks by constructing a model incorporating the flows of information and physical quantities in the network. Using this model we can also show that the cascading phenomenon can be understood as a phase transition in terms of the key parameter characterizing the node capacity. For a parameter value below the phase-transition point, cascading failures can cause the network to disintegrate almost entirely. We will show how to obtain a theoretical estimate for the phase-transition point. The second problem is motivated by the fact that most existing works on the security of complex networks consider attacks on nodes rather than on links. We address attacks on links. Our investigation leads to the finding that many scale-free networks are more sensitive to attacks on short-range than on long-range links. Considering that the small-world phenomenon in complex networks has been identified as being due to the presence of long-range links, i.e., links connecting nodes that would otherwise be separated by a long node-to-node distance, our result, besides its importance concerning network efficiency and security, has the striking implication that the small-world property of scale-free networks is mainly due to short-range links.

  12. 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.

  13. Analysis of complex networks using aggressive abstraction.

    Energy Technology Data Exchange (ETDEWEB)

    Colbaugh, Richard; Glass, Kristin.; Willard, Gerald

    2008-10-01

    This paper presents a new methodology for analyzing complex networks in which the network of interest is first abstracted to a much simpler (but equivalent) representation, the required analysis is performed using the abstraction, and analytic conclusions are then mapped back to the original network and interpreted there. We begin by identifying a broad and important class of complex networks which admit abstractions that are simultaneously dramatically simplifying and property preserving we call these aggressive abstractions -- and which can therefore be analyzed using the proposed approach. We then introduce and develop two forms of aggressive abstraction: 1.) finite state abstraction, in which dynamical networks with uncountable state spaces are modeled using finite state systems, and 2.) onedimensional abstraction, whereby high dimensional network dynamics are captured in a meaningful way using a single scalar variable. In each case, the property preserving nature of the abstraction process is rigorously established and efficient algorithms are presented for computing the abstraction. The considerable potential of the proposed approach to complex networks analysis is illustrated through case studies involving vulnerability analysis of technological networks and predictive analysis for social processes.

  14. Complex cooperative networks from evolutionary preferential attachment.

    Directory of Open Access Journals (Sweden)

    Julia Poncela

    Full Text Available In spite of its relevance to the origin of complex networks, the interplay between form and function and its role during network formation remains largely unexplored. While recent studies introduce dynamics by considering rewiring processes of a pre-existent network, we study network growth and formation by proposing an evolutionary preferential attachment model, its main feature being that the capacity of a node to attract new links depends on a dynamical variable governed in turn by the node interactions. As a specific example, we focus on the problem of the emergence of cooperation by analyzing the formation of a social network with interactions given by the Prisoner's Dilemma. The resulting networks show many features of real systems, such as scale-free degree distributions, cooperative behavior and hierarchical clustering. Interestingly, results such as the cooperators being located mostly on nodes of intermediate degree are very different from the observations of cooperative behavior on static networks. The evolutionary preferential attachment mechanism points to an evolutionary origin of scale-free networks and may help understand similar feedback problems in the dynamics of complex networks by appropriately choosing the game describing the interaction of nodes.

  15. The fundamental structures of dynamic social networks

    CERN Document Server

    Sekara, Vedran; Lehmann, Sune

    2015-01-01

    Networks provide a powerful mathematical framework for analyzing the structure and dynamics of complex systems (1-3). The study of group behavior has deep roots in the social science literature (4,5) and community detection is a central part of modern network science. Network communities have been found to be highly overlapping and organized in a hierarchical structure (6-9). Recent technological advances have provided a toolset for measuring the detailed social dynamics at scale (10,11). In spite of great progress, a quantitative description of the complex temporal behavior of social groups-with dynamics spanning from minute-by-minute changes to patterns expressed on the timescale of years-is still absent. Here we uncover a class of fundamental structures embedded within highly dynamic social networks. On the shortest time-scale, we find that social gatherings are fluid, with members coming and going, but organized via a stable core of individuals. We show that cores represent social contexts (9), with recur...

  16. Vaccination and Complex Social Dynamics

    CERN Document Server

    Mones, Enys; Pentland, Alex; Hupert, Nathaniel; Lehmann, Sune

    2016-01-01

    Vaccination and outbreak monitoring are essential tools for preventing and minimizing outbreaks of infectious diseases. Targeted strategies, where the individuals most important for monitoring or preventing outbreaks are selected for intervention, offer a possibility to significantly improve these measures. Although targeted strategies carry a strong potential, identifying optimal target groups remains a challenge. Here we consider the problem of identifying target groups based on digital communication networks (telecommunication, online social media) in order to predict and contain an infectious disease spreading on a real-world person-to-person network of more than 500 individuals. We show that target groups for efficient outbreak monitoring can be determined based on both telecommunication and online social network information. In case of vaccination the information regarding the digital communication networks improves the efficacy for short-range disease transmissions but, surprisingly, performance is sev...

  17. Temporal correlations in social multiplex networks

    CERN Document Server

    Starnini, Michele; Pastor-Satorras, Romualdo

    2016-01-01

    Social interactions are composite, involve different communication layers and evolve in time. However, a rigorous analysis of the whole complexity of social networks has been hindered so far by lack of suitable data. Here we consider both the multi-layer and dynamic nature of social relations by analysing a diverse set of empirical temporal multiplex networks. We focus on the measurement and characterization of inter-layer correlations to investigate how activity in one layer affects social acts in another layer. We define observables able to detect when genuine correlations are present in empirical data, and single out spurious correlation induced by the bursty nature of human dynamics. We show that such temporal correlations do exist in social interactions where they act to depress the tendency to concentrate long stretches of activity on the same layer and imply some amount of potential predictability in the connection patterns between layers. Our work sets up a general framework to measure temporal correl...

  18. Social networks and the development of social skills in cowbirds.

    Science.gov (United States)

    White, David J; Gersick, Andrew S; Snyder-Mackler, Noah

    2012-07-05

    The complex interrelationships among individuals within social environments can exert selection pressures on social skills: those behaviours and cognitive processes that allow animals to manipulate and out-reproduce others. Social complexity can also have a developmental effect on social skills by providing individuals with opportunities to hone their skills by dealing with the challenges posed in within-group interactions. We examined how social skills develop in captive, adult male brown-headed cowbirds (Molothrus ater) that were exposed to differing levels of 'social complexity' across a 2-year experiment. After each year, subjects housed in groups with dynamic social structure (where many individuals entered and exited the groups during the year) outcompeted birds who had been housed in static groups. Exposure to dynamic structure subsequently led to substantial changes to the social networks of the home conditions during the breeding season. Static groups were characterized by a predictable relationship between singing and reproductive success that was stable across years. In dynamic conditions, however, males showed significant variability in their dominance status, their courting and even in their mating success. Reproductive success of males varied dramatically across years and was responsive to social learning in adulthood, and socially dynamic environments 'trained' individuals to be better competitors, even at an age when the development of many traits important for breeding (like song quality) had ended.

  19. Griffiths phases on complex networks.

    Science.gov (United States)

    Muñoz, Miguel A; Juhász, Róbert; Castellano, Claudio; Odor, Géza

    2010-09-17

    Quenched disorder is known to play a relevant role in dynamical processes and phase transitions. Its effects on the dynamics of complex networks have hardly been studied. Aimed at filling this gap, we analyze the contact process, i.e., the simplest propagation model, with quenched disorder on complex networks. We find Griffiths phases and other rare-region effects, leading rather generically to anomalously slow (algebraic, logarithmic, …) relaxation, on Erdos-Rényi networks. Similar effects are predicted to exist for other topologies with a finite percolation threshold. More surprisingly, we find that Griffiths phases can also emerge in the absence of quenched disorder, as a consequence of topological heterogeneity in networks with finite topological dimension. These results have a broad spectrum of implications for propagation phenomena and other dynamical processes on networks.

  20. Hierarchy measure for complex networks

    CERN Document Server

    Mones, Enys; Vicsek, Tamás

    2012-01-01

    Nature, technology and society are full of complexity arising from the intricate web of the interactions among the units of the related systems (e.g., proteins, computers, people). Consequently, one of the most successful recent approaches to capturing the fundamental features of the structure and dynamics of complex systems has been the investigation of the networks associated with the above units (nodes) together with their relations (edges). Most complex systems have an inherently hierarchical organization and, correspondingly, the networks behind them also exhibit hierarchical features. Indeed, several papers have been devoted to describing this essential aspect of networks, however, without resulting in a widely accepted, converging concept concerning the quantitative characterization of the level of their hierarchy. Here we develop an approach and propose a quantity (measure) which is simple enough to be widely applicable, reveals a number of universal features of the organization of real-world networks...

  1. 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.

  2. Hierarchy Measure for Complex Networks

    Science.gov (United States)

    Mones, Enys; Vicsek, Lilla; Vicsek, Tamás

    2012-01-01

    Nature, technology and society are full of complexity arising from the intricate web of the interactions among the units of the related systems (e.g., proteins, computers, people). Consequently, one of the most successful recent approaches to capturing the fundamental features of the structure and dynamics of complex systems has been the investigation of the networks associated with the above units (nodes) together with their relations (edges). Most complex systems have an inherently hierarchical organization and, correspondingly, the networks behind them also exhibit hierarchical features. Indeed, several papers have been devoted to describing this essential aspect of networks, however, without resulting in a widely accepted, converging concept concerning the quantitative characterization of the level of their hierarchy. Here we develop an approach and propose a quantity (measure) which is simple enough to be widely applicable, reveals a number of universal features of the organization of real-world networks and, as we demonstrate, is capable of capturing the essential features of the structure and the degree of hierarchy in a complex network. The measure we introduce is based on a generalization of the m-reach centrality, which we first extend to directed/partially directed graphs. Then, we define the global reaching centrality (GRC), which is the difference between the maximum and the average value of the generalized reach centralities over the network. We investigate the behavior of the GRC considering both a synthetic model with an adjustable level of hierarchy and real networks. Results for real networks show that our hierarchy measure is related to the controllability of the given system. We also propose a visualization procedure for large complex networks that can be used to obtain an overall qualitative picture about the nature of their hierarchical structure. PMID:22470477

  3. Is the immune network a complex network?

    CERN Document Server

    Souza-e-Silva, Hallan

    2012-01-01

    Some years ago a cellular automata model was proposed to describe the evolution of the immune repertoire of B cells and antibodies based on Jerne's immune network theory and shape-space formalism. Here we investigate if the networks generated by this model in the different regimes can be classified as complex networks. We have found that in the chaotic regime the network has random characteristics with large, constant values of clustering coefficients, while in the ordered phase, the degree distribution of the network is exponential and the clustering coefficient exhibits power law behavior. In the transition region we observed a mixed behavior (random-like and exponential) of the degree distribution as opposed to the scale-free behavior reported for other biological networks. Randomness and low connectivity in the active sites allow for rapid changes in the connectivity distribution of the immune network in order to include and/or discard information and generate a dynamic memory. However it is the availabil...

  4. Organizational networks and social capital

    DEFF Research Database (Denmark)

    Svendsen, Gunnar Lind Haase; Waldstrøm, Christian

    2013-01-01

    This chapter presents a framework for understanding organizational networks and social capital through the lens of “social capital ownership” as well as the private and collective goods provided through this ownership. More specifically, it argues that ownership of social capital in organizations...... is closely connected to four types of social capital – two belonging to the bridging social capital type, and two belonging to the bonding social capital type. The chapter first reviews literature on organizational social capital and then directly focuses on ownership of social capital in organizations......, 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...

  5. Organizational networks and social capital

    DEFF Research Database (Denmark)

    Svendsen, Gunnar Lind Haase; Waldstrøm, Christian

    2013-01-01

    This chapter presents a framework for understanding organizational networks and social capital through the lens of “social capital ownership” as well as the private and collective goods provided through this ownership. More specifically, it argues that ownership of social capital in organizations...... is closely connected to four types of social capital – two belonging to the bridging social capital type, and two belonging to the bonding social capital type. The chapter first reviews literature on organizational social capital and then directly focuses on ownership of social capital in organizations......, 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. Community Detection in Complex Networks

    Institute of Scientific and Technical Information of China (English)

    Nan Du; Bai Wang; Bin Wu

    2008-01-01

    With the rapidly growing evidence that various systems in nature and society can be modeled as complex networks, community detection in networks becomes a hot research topic in physics, sociology, computer society, etc. Although this investigation of community structures has motivated many diverse algorithms, most of them are unsuitable when dealing with large networks due to their computational cost. In this paper, we present a faster algorithm ComTeetor,which is more efficient for the community detection in large complex networks based on the nature of overlapping cliques.This algorithm does not require any priori knowledge about the number or the original division of the communities. With respect to practical applications, ComTector is challenging with five different types of networks including the classic Zachary Karate Club, Scientific Collaboration Network, South Florida Free Word Association Network, Urban Traffic Network, North America Power Grid and the Telecomnmnication Call Network. Experimental results show that our algorithm can discover meaningful communities that meet both the objective basis and our intuitions.

  7. Control efficacy of complex networks

    Science.gov (United States)

    Gao, Xin-Dong; Wang, Wen-Xu; Lai, Ying-Cheng

    2016-06-01

    Controlling complex networks has become a forefront research area in network science and engineering. Recent efforts have led to theoretical frameworks of controllability to fully control a network through steering a minimum set of driver nodes. However, in realistic situations not every node is accessible or can be externally driven, raising the fundamental issue of control efficacy: if driving signals are applied to an arbitrary subset of nodes, how many other nodes can be controlled? We develop a framework to determine the control efficacy for undirected networks of arbitrary topology. Mathematically, based on non-singular transformation, we prove a theorem to determine rigorously the control efficacy of the network and to identify the nodes that can be controlled for any given driver nodes. Physically, we develop the picture of diffusion that views the control process as a signal diffused from input signals to the set of controllable nodes. The combination of mathematical theory and physical reasoning allows us not only to determine the control efficacy for model complex networks and a large number of empirical networks, but also to uncover phenomena in network control, e.g., hub nodes in general possess lower control centrality than an average node in undirected networks.

  8. On Social and Economic Networks

    NARCIS (Netherlands)

    A. Galeotti

    2005-01-01

    textabstractYou can call it a clan, or a network, or a family, or a group of friends. The way you call it is not relevant. What matters is that it exists and often you will need one. A large body of empirical work shows that networks are pervasive in social and economic interactions. This book conta

  9. 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 accu

  10. Maximizing information exchange between complex networks

    Science.gov (United States)

    West, Bruce J.; Geneston, Elvis L.; Grigolini, Paolo

    2008-10-01

    modern research overarching all of the traditional scientific disciplines. The transportation networks of planes, highways and railroads; the economic networks of global finance and stock markets; the social networks of terrorism, governments, businesses and churches; the physical networks of telephones, the Internet, earthquakes and global warming and the biological networks of gene regulation, the human body, clusters of neurons and food webs, share a number of apparently universal properties as the networks become increasingly complex. Ubiquitous aspects of such complex networks are the appearance of non-stationary and non-ergodic statistical processes and inverse power-law statistical distributions. Herein we review the traditional dynamical and phase-space methods for modeling such networks as their complexity increases and focus on the limitations of these procedures in explaining complex networks. Of course we will not be able to review the entire nascent field of network science, so we limit ourselves to a review of how certain complexity barriers have been surmounted using newly applied theoretical concepts such as aging, renewal, non-ergodic statistics and the fractional calculus. One emphasis of this review is information transport between complex networks, which requires a fundamental change in perception that we express as a transition from the familiar stochastic resonance to the new concept of complexity matching.

  11. Maximizing information exchange between complex networks

    Energy Technology Data Exchange (ETDEWEB)

    West, Bruce J. [Mathematical and Information Science, Army Research Office, Research Triangle Park, NC 27708 (United States); Physics Department, Duke University, Durham, NC 27709 (United States)], E-mail: bwest@nc.rr.com; Geneston, Elvis L. [Center for Nonlinear Science, University of North Texas, P.O. Box 311427, Denton, TX 76203-1427 (United States); Physics Department, La Sierra University, 4500 Riverwalk Parkway, Riverside, CA 92515 (United States); Grigolini, Paolo [Center for Nonlinear Science, University of North Texas, P.O. Box 311427, Denton, TX 76203-1427 (United States); Istituto di Processi Chimico Fisici del CNR, Area della Ricerca di Pisa, Via G. Moruzzi, 56124, Pisa (Italy); Dipartimento di Fisica ' E. Fermi' Universita' di Pisa, Largo Pontecorvo 3, 56127 Pisa (Italy)

    2008-10-15

    modern research overarching all of the traditional scientific disciplines. The transportation networks of planes, highways and railroads; the economic networks of global finance and stock markets; the social networks of terrorism, governments, businesses and churches; the physical networks of telephones, the Internet, earthquakes and global warming and the biological networks of gene regulation, the human body, clusters of neurons and food webs, share a number of apparently universal properties as the networks become increasingly complex. Ubiquitous aspects of such complex networks are the appearance of non-stationary and non-ergodic statistical processes and inverse power-law statistical distributions. Herein we review the traditional dynamical and phase-space methods for modeling such networks as their complexity increases and focus on the limitations of these procedures in explaining complex networks. Of course we will not be able to review the entire nascent field of network science, so we limit ourselves to a review of how certain complexity barriers have been surmounted using newly applied theoretical concepts such as aging, renewal, non-ergodic statistics and the fractional calculus. One emphasis of this review is information transport between complex networks, which requires a fundamental change in perception that we express as a transition from the familiar stochastic resonance to the new concept of complexity matching.

  12. A Model of Genetic Variation in Human Social Networks

    CERN Document Server

    Fowler, James H; Christakis, Nicholas A

    2008-01-01

    Social networks influence the evolution of cooperation and they exhibit strikingly systematic patterns across a wide range of human contexts. Both of these facts suggest that variation in the topological attributes of human social networks might have a genetic basis. While genetic variation accounts for a significant portion of the variation in many complex social behaviors, the heritability of egocentric social network attributes is unknown. Here we show that three of these attributes (in-degree, transitivity, and centrality) are heritable. We then develop a "mirror network" method to test extant network models and show that none accounts for observed genetic variation in human social networks. We propose an alternative "attract and introduce" model that generates significant heritability as well as other important network features, and we show that this model with two simple forms of heterogeneity is well suited to the modeling of real social networks in humans. These results suggest that natural selection ...

  13. Ranking in evolving complex networks

    Science.gov (United States)

    Liao, Hao; Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng; Zhou, Ming-Yang

    2017-05-01

    Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google's PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes.

  14. 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…

  15. Simulating social complexity a handbook

    CERN Document Server

    Meyer, Ruth

    2013-01-01

    Social systems are among the most complex known. This poses particular problems for those who wish to understand them. The complexity often makes analytic approaches infeasible and natural language approaches inadequate for relating intricate cause and effect. However, individual- and agent-based computational approaches hold out the possibility of new and deeper understanding of such systems.  Simulating Social Complexity examines all aspects of using agent- or individual-based simulation. This approach represents systems as individual elements having each their own set of differing states and internal processes. The interactions between elements in the simulation represent interactions in the target systems. What makes these elements "social" is that they are usefully interpretable as interacting elements of an observed society. In this, the focus is on human society, but can be extended to include social animals or artificial agents where such work enhances our understanding of human society.  The phenom...

  16. Social contagions on weighted networks

    Science.gov (United States)

    Zhu, Yu-Xiao; Wang, Wei; Tang, Ming; Ahn, Yong-Yeol

    2017-07-01

    We investigate critical behaviors of a social contagion model on weighted networks. An edge-weight compartmental approach is applied to analyze the weighted social contagion on strongly heterogenous networks with skewed degree and weight distributions. We find that degree heterogeneity cannot only alter the nature of contagion transition from discontinuous to continuous but also can enhance or hamper the size of adoption, depending on the unit transmission probability. We also show that the heterogeneity of weight distribution always hinders social contagions, and does not alter the transition type.

  17. Social contagions on weighted networks

    CERN Document Server

    Zhu, Yu-Xiao; Tang, Ming; Ahn, Yong-Yeol

    2016-01-01

    We investigate critical behaviors of a social contagion model on weighted networks. An edge-weight compartmental approach is applied to analyze the weighted social contagion on strongly heterogenous networks with skewed degree and weight distributions. We find that degree heterogeneity can not only alter the nature of contagion transition from discontinuous to continuous but also can enhance or hamper the size of adoption, depending on the unit transmission probability. We also show that, the heterogeneity of weight distribution always hinder social contagions, and does not alter the transition type.

  18. 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.

  19. Vaccines, Contagion, and Social Networks

    CERN Document Server

    Ogburn, Elizabeth L

    2014-01-01

    Consider the causal effect that one individual's treatment may have on another individual's outcome when the outcome is contagious, with specific application to the effect of vaccination on an infectious disease outcome. The effect of one individual's vaccination on another's outcome can be decomposed into two different causal effects, called the "infectiousness" and "contagion" effects. We present identifying assumptions and estimation or testing procedures for infectiousness and contagion effects in two different settings: (1) using data sampled from independent groups of observations, and (2) using data collected from a single interdependent social network. The methods that we propose for social network data require fitting generalized linear models (GLMs). GLMs and other statistical models that require independence across subjects have been used widely to estimate causal effects in social network data, but, because the subjects in networks are presumably not independent, the use of such models is generall...

  20. Cooperation Networks: Endogeneity and Complexity

    CERN Document Server

    Angus, S

    2006-01-01

    Insights from the Complex Systems literature are employed to develop a computational model of truly endogenous strategic network formation. Artificial Adaptive Agents, implemented as Finite State Automata (FSA), play a modified two-player IPD game with an option to further develop the interaction space as part of their strategy. Several insights result from this minor modification: first, I find that network formation is a necessary condition for cooperation to be sustainable but that both the frequency of interaction and the degree to which edge formation impacts agent mixing are both necessary conditions for cooperative networks. Second, within the FSA-modified IPD frame-work, a rich ecology of agents and network topologies is observed and described. Third, the system dynamics are investigated and reveal that initially simple dynamics with small interaction length between agents gives way to complex, a-periodic dynamics with self-organized critical properties when interaction lengths are increased by a sing...

  1. Epidemic spreading in complex networks

    Institute of Scientific and Technical Information of China (English)

    Jie ZHOU; Zong-hua LIU

    2008-01-01

    The study of epidemic spreading in complex networks is currently a hot topic and a large body of results have been achieved.In this paper,we briefly review our contributions to this field,which includes the underlying mechanism of rumor propagation,the epidemic spreading in community networks,the influence of varying topology,and the influence of mobility of agents.Also,some future directions are pointed out.

  2. Measuring multiple evolution mechanisms of complex networks.

    Science.gov (United States)

    Zhang, Qian-Ming; Xu, Xiao-Ke; Zhu, Yu-Xiao; Zhou, Tao

    2015-01-01

    Numerous concise models such as preferential attachment have been put forward to reveal the evolution mechanisms of real-world networks, which show that real-world networks are usually jointly driven by a hybrid mechanism of multiplex features instead of a single pure mechanism. To get an accurate simulation for real networks, some researchers proposed a few hybrid models by mixing multiple evolution mechanisms. Nevertheless, how a hybrid mechanism of multiplex features jointly influence the network evolution is not very clear. In this study, we introduce two methods (link prediction and likelihood analysis) to measure multiple evolution mechanisms of complex networks. Through tremendous experiments on artificial networks, which can be controlled to follow multiple mechanisms with different weights, we find the method based on likelihood analysis performs much better and gives very accurate estimations. At last, we apply this method to some real-world networks which are from different domains (including technology networks and social networks) and different countries (e.g., USA and China), to see how popularity and clustering co-evolve. We find most of them are affected by both popularity and clustering, but with quite different weights.

  3. Assortative model for social networks

    Science.gov (United States)

    Catanzaro, Michele; Caldarelli, Guido; Pietronero, Luciano

    2004-09-01

    In this Brief Report we present a version of a network growth model, generalized in order to describe the behavior of social networks. The case of study considered is the preprint archive at cul.arxiv.org. Each node corresponds to a scientist, and a link is present whenever two authors wrote a paper together. This graph is a nice example of degree-assortative network, that is, to say a network where sites with similar degree are connected to each other. The model presented is one of the few able to reproduce such behavior, giving some insight on the microscopic dynamics at the basis of the graph structure.

  4. Transport optimization on complex networks

    CERN Document Server

    Danila, Bogdan; Marsh, John A; Bassler, Kevin E

    2007-01-01

    We present a comparative study of the application of a recently introduced heuristic algorithm to the optimization of transport on three major types of complex networks. The algorithm balances network traffic iteratively by minimizing the maximum node betweenness with as little path lengthening as possible. We show that by using this optimal routing, a network can sustain significantly higher traffic without jamming than in the case of shortest path routing. A formula is proved that allows quick computation of the average number of hops along the path and of the average travel times once the betweennesses of the nodes are computed. Using this formula, we show that routing optimization preserves the small-world character exhibited by networks under shortest path routing, and that it significantly reduces the average travel time on congested networks with only a negligible increase in the average travel time at low loads. Finally, we study the correlation between the weights of the links in the case of optimal ...

  5. Complex Networks in Psychological Models

    Science.gov (United States)

    Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.

    We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.

  6. Composing Music with Complex Networks

    Science.gov (United States)

    Liu, Xiaofan; Tse, Chi K.; Small, Michael

    In this paper we study the network structure in music and attempt to compose music artificially. Networks are constructed with nodes and edges corresponding to musical notes and their co-occurrences. We analyze sample compositions from Bach, Mozart, Chopin, as well as other types of music including Chinese pop music. We observe remarkably similar properties in all networks constructed from the selected compositions. Power-law exponents of degree distributions, mean degrees, clustering coefficients, mean geodesic distances, etc. are reported. With the network constructed, music can be created by using a biased random walk algorithm, which begins with a randomly chosen note and selects the subsequent notes according to a simple set of rules that compares the weights of the edges, weights of the nodes, and/or the degrees of nodes. The newly created music from complex networks will be played in the presentation.

  7. Remote Synchronization in Complex Networks

    CERN Document Server

    Gambuzza, Lucia Valentina; Fiasconaro, Alessandro; Fortuna, Luigi; Gómez-Gardeñes, Jesús; Frasca, Mattia

    2013-01-01

    We show the existence of a novel dynamical state called remote synchronization in general networks of coupled oscillators. This state is characterized by the synchronization of pairs of nodes that are not directly connected via a physical link or any sequence of synchronized nodes. This phenomenon cannot be observed in networks of phase oscillators as its underlying mechanism is the modulation of the amplitude of those intermediary nodes between the remotely synchronized units. Our findings thus show the ubiquity and robustness of these states and bridge the gap from their recent observation in simple toy graphs to complex networks.

  8. Geographical Effects on Complex Networks

    Institute of Scientific and Technical Information of China (English)

    LIN Zhong-Cai; YANG Lei; YANG Kong-Qing

    2005-01-01

    @@ We investigate how the geographical structure of a complex network affects its network topology, synchronization and the average spatial length of edges. The geographical structure means that the connecting probability of two nodes is related to the spatial distance of the two nodes. Our simulation results show that the geographical structure changes the network topology. The synchronization tendency is enhanced and the average spatial length of edges is enlarged when the node can randomly connect to the further one. Analytic results support our understanding of the phenomena.

  9. Neuronal avalanches in complex networks

    Directory of Open Access Journals (Sweden)

    Victor Hernandez-Urbina

    2016-12-01

    Full Text Available Brain networks are neither regular nor random. Their structure allows for optimal information processing and transmission across the entire neural substrate of an organism. However, for topological features to be appropriately harnessed, brain networks should implement a dynamical regime which prevents phase-locked and chaotic behaviour. Critical neural dynamics refer to a dynamical regime in which the system is poised at the boundary between regularity and randomness. It has been reported that neural systems poised at this boundary achieve maximum computational power. In this paper, we review recent results regarding critical neural dynamics that emerge from systems whose underlying structure exhibits complex network properties.

  10. Complexity reduction of astrochemical networks

    CERN Document Server

    Grassi, T; Gianturco, F A; Baiocchi, P; Merlin, E

    2012-01-01

    We present a new computational scheme aimed at reducing the complexity of the chemical networks in astrophysical models, one which is shown to markedly improve their computational efficiency. It contains a flux-reduction scheme that permits to deal with both large and small systems. This procedure is shown to yield a large speed-up of the corresponding numerical codes and provides good accord with the full network results. We analyse and discuss two examples involving chemistry networks of the interstellar medium and show that the results from the present reduction technique reproduce very well the results from fuller calculations.

  11. Assessing Group Interaction with Social Language Network Analysis

    Science.gov (United States)

    Scholand, Andrew J.; Tausczik, Yla R.; Pennebaker, James W.

    In this paper we discuss a new methodology, social language network analysis (SLNA), that combines tools from social language processing and network analysis to assess socially situated working relationships within a group. Specifically, SLNA aims to identify and characterize the nature of working relationships by processing artifacts generated with computer-mediated communication systems, such as instant message texts or emails. Because social language processing is able to identify psychological, social, and emotional processes that individuals are not able to fully mask, social language network analysis can clarify and highlight complex interdependencies between group members, even when these relationships are latent or unrecognized.

  12. Controlling centrality in complex networks

    Science.gov (United States)

    Nicosia, V.; Criado, R.; Romance, M.; Russo, G.; Latora, V.

    2012-01-01

    Spectral centrality measures allow to identify influential individuals in social groups, to rank Web pages by popularity, and even to determine the impact of scientific researches. The centrality score of a node within a network crucially depends on the entire pattern of connections, so that the usual approach is to compute node centralities once the network structure is assigned. We face here with the inverse problem, that is, we study how to modify the centrality scores of the nodes by acting on the structure of a given network. We show that there exist particular subsets of nodes, called controlling sets, which can assign any prescribed set of centrality values to all the nodes of a graph, by cooperatively tuning the weights of their out-going links. We found that many large networks from the real world have surprisingly small controlling sets, containing even less than 5 – 10% of the nodes. PMID:22355732

  13. 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.

  14. Markovian Dynamics on Complex Reaction Networks

    CERN Document Server

    Goutsias, John

    2012-01-01

    Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underling population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions, the computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating...

  15. Community Detection in Quantum Complex Networks

    CERN Document Server

    Faccin, Mauro; Johnson, Tomi; Biamonte, Jacob; Bergholm, Ville

    2013-01-01

    Determining community structure in interacting systems, ranging from technological to social, from biological to chemical, is a topic of central importance in the study of networks. Extending this concept to apply to quantum systems represents an open challenge and a crucial missing component towards a theory of complex networks based on quantum mechanics. Here we accomplish this goal by introducing methods for identifying the community structure of a network governed by quantum dynamics. To illustrate our approach we turn to a host of examples, including a naturally occurring light-harvesting network, where from first principles we determine a consistent community structure. In certain regimes the communities we determine agree with a partitioning currently done by hand in the quantum chemistry literature. In other regimes, we uncover a new community structure. The difference stems from defining measures to determine distances between nodes in quantum systems, and then determining optimal modularity. Merging...

  16. 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.

  17. 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.

  18. Visualization Through Knowledge Representation Model for Social Networks

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar; Athar Javed, Muhammad; Ahmed, Zaki

    2011-01-01

    the process of knowing, learning and creating knowledge is the relevant aspect (Nonaka and Takeuchi 1995). In this paper knowledge representation is presented in 3D style for the understanding and visualization of dynamics of complex social networks by developing a TANetworkTool (Task Analysis Network Tool......). The standard or normal representation of a typical social network is through a graph data structure in 2D. The dynamics of larger social networks is so complex some time it becomes difficult to understand the various levels of interactions and dependencies just by mere representation through a tree or graph...... of complex social networks and complimenting the analytical results. This representation can also help authorities not necessarily having specific scientific background to understand and perhaps take preventive actions required in certain specific scenarios for example dealing with terrorist/covert networks....

  19. NEXCADE: perturbation analysis for complex networks.

    Directory of Open Access Journals (Sweden)

    Gitanjali Yadav

    Full Text Available Recent advances in network theory have led to considerable progress in our understanding of complex real world systems and their behavior in response to external threats or fluctuations. Much of this research has been invigorated by demonstration of the 'robust, yet fragile' nature of cellular and large-scale systems transcending biology, sociology, and ecology, through application of the network theory to diverse interactions observed in nature such as plant-pollinator, seed-dispersal agent and host-parasite relationships. In this work, we report the development of NEXCADE, an automated and interactive program for inducing disturbances into complex systems defined by networks, focusing on the changes in global network topology and connectivity as a function of the perturbation. NEXCADE uses a graph theoretical approach to simulate perturbations in a user-defined manner, singly, in clusters, or sequentially. To demonstrate the promise it holds for broader adoption by the research community, we provide pre-simulated examples from diverse real-world networks including eukaryotic protein-protein interaction networks, fungal biochemical networks, a variety of ecological food webs in nature as well as social networks. NEXCADE not only enables network visualization at every step of the targeted attacks, but also allows risk assessment, i.e. identification of nodes critical for the robustness of the system of interest, in order to devise and implement context-based strategies for restructuring a network, or to achieve resilience against link or node failures. Source code and license for the software, designed to work on a Linux-based operating system (OS can be downloaded at http://www.nipgr.res.in/nexcade_download.html. In addition, we have developed NEXCADE as an OS-independent online web server freely available to the scientific community without any login requirement at http://www.nipgr.res.in/nexcade.html.

  20. Complex-Valued Neural Networks

    CERN Document Server

    Hirose, Akira

    2012-01-01

    This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published in 2006, which lends itself to graduate and undergraduate courses in electrical engineering, informatics, control engineering, mechanics, robotics, bioengineering, and other relevant fields. In the second edition the recent trends in CVNNs research are included, resulting in e.g. almost a doubled number of references. The parametron invented in 1954 is also referred to with discussion on analogy and disparity. Also various additional arguments on the advantages of the complex-valued neural networks enhancing the difference to real-valued neural networks are given in various sections. The book is useful for those beginning their studies, for instance, in adaptive signal processing for highly functional sensing and imaging, control in unknown and changing environment, robotics inspired by human neural systems, and brain-like information processing, as well as interdisciplina...

  1. 5th International Workshop on Complex Networks and their Applications

    CERN Document Server

    Gaito, Sabrina; Quattrociocchi, Walter; Sala, Alessandra

    2017-01-01

    This book highlights cutting-edge research in the field of network science, offering scientists, researchers and graduate students a unique opportunity to catch up on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the fifth International Workshop on Complex Networks & their Applications (COMPLEX NETWORKS 2016), which took place in Milan during the last week of November 2016. The carefully selected papers are divided into 11 sections reflecting the diversity and richness of research areas in the field. More specifically, the following topics are covered: Network models; Network measures; Community structure; Network dynamics; Diffusion, epidemics and spreading processes; Resilience and control; Network visualization; Social and political networks; Networks in finance and economics; Biological and ecological networks; and Network analysis.

  2. 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.

  3. Social Networks as Marketing Tools

    Directory of Open Access Journals (Sweden)

    NOZHA ERRAGCHA

    2014-05-01

    Full Text Available The aims of this paper is to reinforce the literature on the digital social networks and their influences on the marketing Having presented and categorized the digital social, networks, we highlighted, the opportunities which brings Web2.0 to the marketing. The advent of Web2.0 imposed fundamental changes Which required the revalorization of the role of the consumer in the marketing approach. Indeed, this one is not passive any more, but it becomes a co-value-creating for the company

  4. Wealth dynamics on complex networks

    Science.gov (United States)

    Garlaschelli, Diego; Loffredo, Maria I.

    2004-07-01

    We study a model of wealth dynamics (Physica A 282 (2000) 536) which mimics transactions among economic agents. The outcomes of the model are shown to depend strongly on the topological properties of the underlying transaction network. The extreme cases of a fully connected and a fully disconnected network yield power-law and log-normal forms of the wealth distribution, respectively. We perform numerical simulations in order to test the model on more complex network topologies. We show that the mixed form of most empirical distributions (displaying a non-smooth transition from a log-normal to a power-law form) can be traced back to a heterogeneous topology with varying link density, which on the other hand is a recently observed property of real networks.

  5. Optimal Disruption of Complex Networks

    CERN Document Server

    Zhao, Jin-Hua

    2016-01-01

    The collection of all the strongly connected components in a directed graph, among each cluster of which any node has a path to another node, is a typical example of the intertwining structure and dynamics in complex networks, as its relative size indicates network cohesion and it also composes of all the feedback cycles in the network. Here we consider finding an optimal strategy with minimal effort in removal arcs (for example, deactivation of directed interactions) to fragment all the strongly connected components into tree structure with no effect from feedback mechanism. We map the optimal network disruption problem to the minimal feedback arc set problem, a non-deterministically polynomial hard combinatorial optimization problem in graph theory. We solve the problem with statistical physical methods from spin glass theory, resulting in a simple numerical method to extract sub-optimal disruption arc sets with significantly better results than a local heuristic method and a simulated annealing method both...

  6. Dynamics in online social networks

    CERN Document Server

    Grabowicz, Przemyslaw A; Eguiluz, Victor M

    2012-01-01

    An increasing number of today's social interactions occurs using online social media as communication channels. Some online social networks have become extremely popular in the last decade. They differ among themselves in the character of the service they provide to online users. For instance, Facebook can be seen mainly as a platform for keeping in touch with close friends and relatives, Twitter is used to propagate and receive news, LinkedIn facilitates the maintenance of professional contacts, Flickr gathers amateurs and professionals of photography, etc. Albeit different, all these online platforms share an ingredient that pervades all their applications. There exists an underlying social network that allows their users to keep in touch with each other and helps to engage them in common activities or interactions leading to a better fulfillment of the service's purposes. This is the reason why these platforms share a good number of functionalities, e.g., personal communication channels, broadcasted status...

  7. 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…

  8. 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…

  9. The complex network of musical tastes

    Science.gov (United States)

    Buldú, Javier M.; Cano, P.; Koppenberger, M.; Almendral, Juan A.; Boccaletti, S.

    2007-06-01

    We present an empirical study of the evolution of a social network constructed under the influence of musical tastes. The network is obtained thanks to the selfless effort of a broad community of users who share playlists of their favourite songs with other users. When two songs co-occur in a playlist a link is created between them, leading to a complex network where songs are the fundamental nodes. In this representation, songs in the same playlist could belong to different musical genres, but they are prone to be linked by a certain musical taste (e.g. if songs A and B co-occur in several playlists, an user who likes A will probably like also B). Indeed, playlist collections such as the one under study are the basic material that feeds some commercial music recommendation engines. Since playlists have an input date, we are able to evaluate the topology of this particular complex network from scratch, observing how its characteristic parameters evolve in time. We compare our results with those obtained from an artificial network defined by means of a null model. This comparison yields some insight on the evolution and structure of such a network, which could be used as ground data for the development of proper models. Finally, we gather information that can be useful for the development of music recommendation engines and give some hints about how top-hits appear.

  10. Complex networks for streamflow dynamics

    Directory of Open Access Journals (Sweden)

    B. Sivakumar

    2014-07-01

    Full Text Available Streamflow modeling is an enormously challenging problem, due to the complex and nonlinear interactions between climate inputs and landscape characteristics over a wide range of spatial and temporal scales. A basic idea in streamflow studies is to establish connections that generally exist, but attempts to identify such connections are largely dictated by the problem at hand and the system components in place. While numerous approaches have been proposed in the literature, our understanding of these connections remains far from adequate. The present study introduces the theory of networks, and in particular complex networks, to examine the connections in streamflow dynamics, with a particular focus on spatial connections. Monthly streamflow data observed over a period of 52 years from a large network of 639 monitoring stations in the contiguous United States are studied. The connections in this streamflow network are examined using the concept of clustering coefficient, which is a measure of local density and quantifies the network's tendency to cluster. The clustering coefficient analysis is performed with several different threshold levels, which are based on correlations in streamflow data between the stations. The clustering coefficient values of the 639 stations are used to obtain important information about the connections in the network and their extent, similarity and differences between stations/regions, and the influence of thresholds. The relationship of the clustering coefficient with the number of links/actual links in the network and the number of neighbors is also addressed. The results clearly indicate the usefulness of the network-based approach for examining connections in streamflow, with important implications for interpolation and extrapolation, classification of catchments, and predictions in ungaged basins.

  11. Multilevel Complex Networks and Systems

    Science.gov (United States)

    Caldarelli, Guido

    2014-03-01

    Network theory has been a powerful tool to model isolated complex systems. However, the classical approach does not take into account the interactions often present among different systems. Hence, the scientific community is nowadays concentrating the efforts on the foundations of new mathematical tools for understanding what happens when multiple networks interact. The case of economic and financial networks represents a paramount example of multilevel networks. In the case of trade, trade among countries the different levels can be described by the different granularity of the trading relations. Indeed, we have now data from the scale of consumers to that of the country level. In the case of financial institutions, we have a variety of levels at the same scale. For example one bank can appear in the interbank networks, ownership network and cds networks in which the same institution can take place. In both cases the systemically important vertices need to be determined by different procedures of centrality definition and community detection. In this talk I will present some specific cases of study related to these topics and present the regularities found. Acknowledged support from EU FET Project ``Multiplex'' 317532.

  12. Group Recommendation in Social Networks

    Science.gov (United States)

    2011-01-01

    the Facebook social graph are connected to each other via relationships. Bret Taylor is a fan of the Coca - Cola page, and Bret Taylor and Arjun...even used for business promotions like organizing events and taking surveys etc. Consider for example, if you would like to conduct a survey it...takes a lot of effort in terms of the promotion to reach out to the intended audience. Using social networks targeting the audience and reaching out

  13. 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

  14. Analyzing covert social network foundation behind terrorism disaster

    CERN Document Server

    Maeno, Yoshiharu

    2007-01-01

    This paper addresses a method to analyze the covert social network foundation hidden behind the terrorism disaster. It is to solve a node discovery problem, which means to discover a node, which functions relevantly in a social network, but escaped from monitoring on the presence and mutual relationship of nodes. The method aims at integrating the expert investigator's prior understanding, insight on the terrorists' social network nature derived from the complex graph theory, and computational data processing. The social network responsible for the 9/11 attack in 2001 is used to execute simulation experiment to evaluate the performance of the method.

  15. The Kuramoto model in complex networks

    Science.gov (United States)

    Rodrigues, Francisco A.; Peron, Thomas K. DM.; Ji, Peng; Kurths, Jürgen

    2016-01-01

    Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from social and physical to biological and technological systems. The most successful approach to describe how coherent behavior emerges in these complex systems is given by the paradigmatic Kuramoto model. This model has been traditionally studied in complete graphs. However, besides being intrinsically dynamical, complex systems present very heterogeneous structure, which can be represented as complex networks. This report is dedicated to review main contributions in the field of synchronization in networks of Kuramoto oscillators. In particular, we provide an overview of the impact of network patterns on the local and global dynamics of coupled phase oscillators. We cover many relevant topics, which encompass a description of the most used analytical approaches and the analysis of several numerical results. Furthermore, we discuss recent developments on variations of the Kuramoto model in networks, including the presence of noise and inertia. The rich potential for applications is discussed for special fields in engineering, neuroscience, physics and Earth science. Finally, we conclude by discussing problems that remain open after the last decade of intensive research on the Kuramoto model and point out some promising directions for future research.

  16. 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.

  17. 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.

  18. Social networks and factor markets

    DEFF Research Database (Denmark)

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

    2017-01-01

    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...

  19. Data Mining on Social Interaction Networks

    OpenAIRE

    Atzmueller, Martin

    2013-01-01

    Social media and social networks have already woven themselves into the very fabric of everyday life. This results in a dramatic increase of social data capturing various relations between the users and their associated artifacts, both in online networks and the real world using ubiquitous devices. In this work, we consider social interaction networks from a data mining perspective - also with a special focus on real-world face-to-face contact networks: We combine data mining and social netwo...

  20. Physical controllability of complex networks

    Science.gov (United States)

    Wang, Le-Zhi; Chen, Yu-Zhong; Wang, Wen-Xu; Lai, Ying-Cheng

    2017-01-01

    A challenging problem in network science is to control complex networks. In existing frameworks of structural or exact controllability, the ability to steer a complex network toward any desired state is measured by the minimum number of required driver nodes. However, if we implement actual control by imposing input signals on the minimum set of driver nodes, an unexpected phenomenon arises: due to computational or experimental error there is a great probability that convergence to the final state cannot be achieved. In fact, the associated control cost can become unbearably large, effectively preventing actual control from being realized physically. The difficulty is particularly severe when the network is deemed controllable with a small number of drivers. Here we develop a physical controllability framework based on the probability of achieving actual control. Using a recently identified fundamental chain structure underlying the control energy, we offer strategies to turn physically uncontrollable networks into physically controllable ones by imposing slightly augmented set of input signals on properly chosen nodes. Our findings indicate that, although full control can be theoretically guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control cost to achieve physical control. PMID:28074900

  1. Physical controllability of complex networks

    Science.gov (United States)

    Wang, Le-Zhi; Chen, Yu-Zhong; Wang, Wen-Xu; Lai, Ying-Cheng

    2017-01-01

    A challenging problem in network science is to control complex networks. In existing frameworks of structural or exact controllability, the ability to steer a complex network toward any desired state is measured by the minimum number of required driver nodes. However, if we implement actual control by imposing input signals on the minimum set of driver nodes, an unexpected phenomenon arises: due to computational or experimental error there is a great probability that convergence to the final state cannot be achieved. In fact, the associated control cost can become unbearably large, effectively preventing actual control from being realized physically. The difficulty is particularly severe when the network is deemed controllable with a small number of drivers. Here we develop a physical controllability framework based on the probability of achieving actual control. Using a recently identified fundamental chain structure underlying the control energy, we offer strategies to turn physically uncontrollable networks into physically controllable ones by imposing slightly augmented set of input signals on properly chosen nodes. Our findings indicate that, although full control can be theoretically guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control cost to achieve physical control.

  2. Markovian dynamics on complex reaction networks

    Energy Technology Data Exchange (ETDEWEB)

    Goutsias, J., E-mail: goutsias@jhu.edu; Jenkinson, G., E-mail: jenkinson@jhu.edu

    2013-08-10

    Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples.

  3. Purity homophily in social networks.

    Science.gov (United States)

    Dehghani, Morteza; Johnson, Kate; Hoover, Joe; Sagi, Eyal; Garten, Justin; Parmar, Niki Jitendra; Vaisey, Stephen; Iliev, Rumen; Graham, Jesse

    2016-03-01

    Does sharing moral values encourage people to connect and form communities? The importance of moral homophily (love of same) has been recognized by social scientists, but the types of moral similarities that drive this phenomenon are still unknown. Using both large-scale, observational social-media analyses and behavioral lab experiments, the authors investigated which types of moral similarities influence tie formations. Analysis of a corpus of over 700,000 tweets revealed that the distance between 2 people in a social-network can be predicted based on differences in the moral purity content-but not other moral content-of their messages. The authors replicated this finding by experimentally manipulating perceived moral difference (Study 2) and similarity (Study 3) in the lab and demonstrating that purity differences play a significant role in social distancing. These results indicate that social network processes reflect moral selection, and both online and offline differences in moral purity concerns are particularly predictive of social distance. This research is an attempt to study morality indirectly using an observational big-data study complemented with 2 confirmatory behavioral experiments carried out using traditional social-psychology methodology.

  4. 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…

  5. 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…

  6. Node Classification in Social Networks

    Science.gov (United States)

    Bhagat, Smriti; Cormode, Graham; Muthukrishnan, S.

    When dealing with large graphs, such as those that arise in the context of online social networks, a subset of nodes may be labeled. These labels can indicate demographic values, interest, beliefs or other characteristics of the nodes (users). A core problem is to use this information to extend the labeling so that all nodes are assigned a label (or labels).

  7. Critical Transitions in Social Network Activity

    DEFF Research Database (Denmark)

    Kuehn, Christian; Martens, Erik Andreas; Romero, Daniel M

    2014-01-01

    A large variety of complex systems in ecology, climate science, biomedicine and engineering have been observed to exhibit tipping points, where the dynamical state of the system abruptly changes. For example, such critical transitions may result in the sudden change of ecological environments...... a priori known events are preceded by variance and autocorrelation growth. Our findings thus clearly establish the necessary starting point to further investigate the relationship between abstract mathematical theory and various classes of critical transitions in social networks....

  8. Nonparametric Bayesian Modeling of Complex Networks

    DEFF Research Database (Denmark)

    Schmidt, Mikkel Nørgaard; Mørup, Morten

    2013-01-01

    Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...... for complex networks can be derived and point out relevant literature....

  9. Statistical physics of complex networks

    Science.gov (United States)

    Xie, Huafeng

    We live in a connected world. It is of great practical importance and intellectual appeal to understand the networks surrounding us. In this work we study ranking of the nodes in complex networks. In large networks such as World Wide Web (WWW) and citation networks of scientific literature, searching by keywords is a common practice to retrieve useful information. On the WWW, apart from the contents of webpages, the topology of the network itself can be a rich source of information about their relative importance and relevancy to the search query. It is the effective utilization of this topological information [50] which advanced the Google search engine to its present position of the most popular tool on the WWW. The World-Wide Web (WWW) is characterized by a strong community structure in which communities of webpages are densely interconnected by hyperlinks. We study how such network architecture affects the average Google ranking of individual webpages in the community. Using a mean-field approximation, we quantify how the average Google rank of community's webpages depends on the degree to which it is isolated from the rest of the world in both incoming and outgoing directions, and alpha -- the only intrinsic parameter of Google's PageRank algorithm. We proceed with numerical study of simulated networks and empirical study of several internal web-communities within two US universities. The predictions of our mean-field treatment were qualitatively verified in those real-life networks. Furthermore, the value alpha = 0.15 used by Google seems to be optimized for the degree of isolation of communities as they exist in the actual WWW. We then extend Google's PageRank algorithm to citation networks of scientific literature. Unlike hyperlinks, citations cannot be updated after the point of publication. This results in strong aging characteristics of citation networks that affect the performance of the PageRank algorithm. To rectify this we modify the Page

  10. 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.

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

    Science.gov (United States)

    Ilany, Amiyaal; Akçay, Erol

    2016-06-28

    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.

  12. 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

  13. Preferential urn model and nongrowing complex networks.

    Science.gov (United States)

    Ohkubo, Jun; Yasuda, Muneki; Tanaka, Kazuyuki

    2005-12-01

    A preferential urn model, which is based on the concept "the rich get richer," is proposed. From a relationship between a nongrowing model for complex networks and the preferential urn model in regard to degree distributions, it is revealed that a fitness parameter in the nongrowing model is interpreted as an inverse local temperature in the preferential urn model. Furthermore, it is clarified that the preferential urn model with randomness generates a fat-tailed occupation distribution; the concept of the local temperature enables us to understand the fat-tailed occupation distribution intuitively. Since the preferential urn model is a simple stochastic model, it can be applied to research on not only the nongrowing complex networks, but also many other fields such as econophysics and social sciences.

  14. Consensus clustering in complex networks

    CERN Document Server

    Lancichinetti, Andrea; 10.1038/srep00336

    2012-01-01

    The community structure of complex networks reveals both their organization and hidden relationships among their constituents. Most community detection methods currently available are not deterministic, and their results typically depend on the specific random seeds, initial conditions and tie-break rules adopted for their execution. Consensus clustering is used in data analysis to generate stable results out of a set of partitions delivered by stochastic methods. Here we show that consensus clustering can be combined with any existing method in a self-consistent way, enhancing considerably both the stability and the accuracy of the resulting partitions. This framework is also particularly suitable to monitor the evolution of community structure in temporal networks. An application of consensus clustering to a large citation network of physics papers demonstrates its capability to keep track of the birth, death and diversification of topics.

  15. Nested subgraphs of complex networks

    Energy Technology Data Exchange (ETDEWEB)

    Corominas-Murtra, Bernat; Sole, Ricard V [ICREA-Complex Systems Lab, Universitat Pompeu Fabra, Dr Aiguader 80, 08003 Barcelona (Spain); Mendes, Jose F F [Departamento de Fisica da Universidade de Aveiro, 3810-193 Aveiro (Portugal)], E-mail: bernat.corominas@upf.edu

    2008-09-26

    We analytically explore the scaling properties of a general class of nested subgraphs in complex networks, which includes the K-core and the K-scaffold, among others. We name such a class of subgraphs K-nested subgraphs since they generate families of subgraphs such that ...S{sub K+1}(G) subset or equal S{sub K}(G) subset or equal S{sub K-1}(G).... Using the so-called configuration model it is shown that any family of nested subgraphs over a network with diverging second moment and finite first moment has infinite elements (i.e. lacking a percolation threshold). Moreover, for a scale-free network with the above properties, we show that any nested family of subgraphs is self-similar by looking at the degree distribution. Both numerical simulations and real data are analyzed and display good agreement with our theoretical predictions.

  16. Degree correlations in signed social networks

    Science.gov (United States)

    Ciotti, Valerio; Bianconi, Ginestra; Capocci, Andrea; Colaiori, Francesca; Panzarasa, Pietro

    2015-03-01

    We investigate degree correlations in two online social networks where users are connected through different types of links. We find that, while subnetworks in which links have a positive connotation, such as endorsement and trust, are characterized by assortative mixing by degree, networks in which links have a negative connotation, such as disapproval and distrust, are characterized by disassortative patterns. We introduce a class of simple theoretical models to analyze the interplay between network topology and the superimposed structure based on the sign of links. Results uncover the conditions that underpin the emergence of the patterns observed in the data, namely the assortativity of positive subnetworks and the disassortativity of negative ones. We discuss the implications of our study for the analysis of signed complex networks.

  17. Degree correlations in signed social networks

    CERN Document Server

    Ciotti, Valerio; Capocci, Andrea; Colaiori, Francesca; Panzarasa, Pietro

    2014-01-01

    We investigate degree correlations in two online social networks where users are connected through different types of links. We find that, while subnetworks in which links have a positive connotation, such as endorsement and trust, are characterized by assortative mixing by degree, networks in which links have a negative connotation, such as disapproval and distrust, are characterized by disassortative patterns. We introduce a class of simple theoretical models to analyze the interplay between network topology and the superimposed structure based on the sign of links. Results uncover the conditions that underpin the emergence of the patterns observed in the data, namely the assortativity of positive subnetworks and the disassortativity of negative ones. We discuss the implications of our study for the analysis of signed complex networks.

  18. Theoretical research progress in complexity of complex dynamical networks

    Institute of Scientific and Technical Information of China (English)

    Fang Jinqing

    2007-01-01

    This article reviews the main progress in dynamical complexity of theoretical models for nonlinear complex networks proposed by our Joint Complex Network Research Group (JCNRG). The topological and dynamical properties of these theoretical models are numerically and analytically studied. Several findings are useful for understanding and deeply studying complex networks from macroscopic to microscopic levels and have a potential of applications in real-world networks.

  19. Bell Inequalities for Complex Networks

    Science.gov (United States)

    2015-10-26

    AFRL-AFOSR-VA-TR-2015-0355 YIP Bell Inequalities for Complex Networks Greg Ver Steeg UNIVERSITY OF SOUTHERN CALIFORNIA LOS ANGELES Final Report 10/26...Period: 1 August 2012 to 31 July 2015 Information Sciences Institute University of Southern California, 4676 Admiralty Way Marina del Rey, CA 90292...Machine Intelligence and Autonomy ” in 2014. Besides these Air Force affiliated interactions, I disseminated results of this effort in standard academic

  20. 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.

  1. Identification of hybrid node and link communities in complex networks

    Science.gov (United States)

    He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong

    2015-03-01

    Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.

  2. Masculinity, Educational Achievement and Social Status: A Social Network Analysis

    Science.gov (United States)

    Lusher, Dean

    2011-01-01

    This study utilises a quantitative case study social network approach to explore the connection between masculinity and scholastic achievement in two secondary, all-boys schools in Australia. In both schools two social networks representing social status are explored: the "friendship" network as a measure of status that includes…

  3. Community Detection in Quantum Complex Networks

    Science.gov (United States)

    Faccin, Mauro; Migdał, Piotr; Johnson, Tomi H.; Bergholm, Ville; Biamonte, Jacob D.

    2014-10-01

    Determining community structure is a central topic in the study of complex networks, be it technological, social, biological or chemical, static or in interacting systems. In this paper, we extend the concept of community detection from classical to quantum systems—a crucial missing component of a theory of complex networks based on quantum mechanics. We demonstrate that certain quantum mechanical effects cannot be captured using current classical complex network tools and provide new methods that overcome these problems. Our approaches are based on defining closeness measures between nodes, and then maximizing modularity with hierarchical clustering. Our closeness functions are based on quantum transport probability and state fidelity, two important quantities in quantum information theory. To illustrate the effectiveness of our approach in detecting community structure in quantum systems, we provide several examples, including a naturally occurring light-harvesting complex, LHCII. The prediction of our simplest algorithm, semiclassical in nature, mostly agrees with a proposed partitioning for the LHCII found in quantum chemistry literature, whereas our fully quantum treatment of the problem uncovers a new, consistent, and appropriately quantum community structure.

  4. Measurement methods on the complexity of network

    Institute of Scientific and Technical Information of China (English)

    LIN Lin; DING Gang; CHEN Guo-song

    2010-01-01

    Based on the size of network and the number of paths in the network,we proposed a model of topology complexity of a network to measure the topology complexity of the network.Based on the analyses of the effects of the number of the equipment,the types of equipment and the processing time of the node on the complexity of the network with the equipment-constrained,a complexity model of equipment-constrained network was constructed to measure the integrated complexity of the equipment-constrained network.The algorithms for the two models were also developed.An automatic generator of the random single label network was developed to test the models.The results show that the models can correctly evaluate the topology complexity and the integrated complexity of the networks.

  5. 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....

  6. Privacy and Security: Online Social Networking

    Directory of Open Access Journals (Sweden)

    Akriti Verma, Deepak Kshirsagar, Sana Khan

    2013-03-01

    Full Text Available Online Social Networking (OSN sites such asFacebook, Twitter, Google+ attract hundreds andmillions of users. Such social networks have acentralized architecture wherein user's private dataand user generated content are centrally owned by asingle administrative domain that managescommunication between its users. As a result,centralized social networks have gatheredunprecedented amounts of data about the behaviorsand personalities of individuals, raising majorprivacy and security concerns. This has put indemand for a decentralized social networking sitethat addresses the privacy and security issues.

  7. Benford’s Distribution in Complex Networks

    Science.gov (United States)

    Morzy, Mikołaj; Kajdanowicz, Tomasz; Szymański, Bolesław K.

    2016-10-01

    Many collections of numbers do not have a uniform distribution of the leading digit, but conform to a very particular pattern known as Benford’s distribution. This distribution has been found in numerous areas such as accounting data, voting registers, census data, and even in natural phenomena. Recently it has been reported that Benford’s law applies to online social networks. Here we introduce a set of rigorous tests for adherence to Benford’s law and apply it to verification of this claim, extending the scope of the experiment to various complex networks and to artificial networks created by several popular generative models. Our findings are that neither for real nor for artificial networks there is sufficient evidence for common conformity of network structural properties with Benford’s distribution. We find very weak evidence suggesting that three measures, degree centrality, betweenness centrality and local clustering coefficient, could adhere to Benford’s law for scalefree networks but only for very narrow range of their parameters.

  8. Controlling centrality in complex networks

    CERN Document Server

    Nicosia, Vincenzo; Romance, Miguel; Russo, Giovanni; Latora, Vito

    2011-01-01

    Spectral centrality measures allow to identify influential individuals in social groups, to rank Web pages by their popularity, and even to determine the impact of scientific researches. The centrality score of a node within a network crucially depends on the entire pattern of connections, so that the usual approach is to compute the node centralities once the network structure is assigned. We face here with the inverse problem, that is, we study how to modify the centrality scores of the nodes by acting on the structure of a given network. We prove that there exist particular subsets of nodes, called controlling sets, which can assign any prescribed set of centrality values to all the nodes of a graph, by cooperatively tuning the weights of their out-going links. We show that many large networks from the real world have surprisingly small controlling sets, containing even less than 5-10% of the nodes. These results suggest that rankings obtained from spectral centrality measures have to be considered with ex...

  9. Exploring Impact: Negative Effects of Social Networks

    OpenAIRE

    Egbert, Henrik; Sedlarski, Teodor

    2011-01-01

    he sociological literature on social networks emphasizes by and large positive network effects. Negative effects of such networks are discussed rather rarely. This paper tackles negative effects by applying economic theory, particularly neoclassical theory, new institutional theory and the results from experimental economics to the concept of social networks. In the paper it is assumed that social networks are exclusive and since exclusiveness affects the allocation of resources, negative ext...

  10. 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

  11. Topological evolution of virtual social networks by modeling social activities

    Science.gov (United States)

    Sun, Xin; Dong, Junyu; Tang, Ruichun; Xu, Mantao; Qi, Lin; Cai, Yang

    2015-09-01

    With the development of Internet and wireless communication, virtual social networks are becoming increasingly important in the formation of nowadays' social communities. Topological evolution model is foundational and critical for social network related researches. Up to present most of the related research experiments are carried out on artificial networks, however, a study of incorporating the actual social activities into the network topology model is ignored. This paper first formalizes two mathematical abstract concepts of hobbies search and friend recommendation to model the social actions people exhibit. Then a social activities based topology evolution simulation model is developed to satisfy some well-known properties that have been discovered in real-world social networks. Empirical results show that the proposed topology evolution model has embraced several key network topological properties of concern, which can be envisioned as signatures of real social networks.

  12. 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…

  13. Challenges for Mobile Social Networking Applications

    Science.gov (United States)

    Rana, Juwel; Kristiansson, Johan; Hallberg, Josef; Synnes, Kåre

    This paper presents work in progress regarding utilization of social network information for mobile applications. Primarily a number of challenges are identified, such as how to mine data from multiple social networks, how to integrate and consolidate social networks, and how to manage semantic information for mobile applications. The challenges are discussed from a semantic Web perspective using a driving scenario as motivation.

  14. Using learning networks to understand complex systems: a case study of biological, geophysical and social research in the Amazon.

    Science.gov (United States)

    Barlow, Jos; Ewers, Robert M; Anderson, Liana; Aragao, Luiz E O C; Baker, Tim R; Boyd, Emily; Feldpausch, Ted R; Gloor, Emanuel; Hall, Anthony; Malhi, Yadvinder; Milliken, William; Mulligan, Mark; Parry, Luke; Pennington, Toby; Peres, Carlos A; Phillips, Oliver L; Roman-Cuesta, Rosa Maria; Tobias, Joseph A; Gardner, Toby A

    2011-05-01

    Developing high-quality scientific research will be most effective if research communities with diverse skills and interests are able to share information and knowledge, are aware of the major challenges across disciplines, and can exploit economies of scale to provide robust answers and better inform policy. We evaluate opportunities and challenges facing the development of a more interactive research environment by developing an interdisciplinary synthesis of research on a single geographic region. We focus on the Amazon as it is of enormous regional and global environmental importance and faces a highly uncertain future. To take stock of existing knowledge and provide a framework for analysis we present a set of mini-reviews from fourteen different areas of research, encompassing taxonomy, biodiversity, biogeography, vegetation dynamics, landscape ecology, earth-atmosphere interactions, ecosystem processes, fire, deforestation dynamics, hydrology, hunting, conservation planning, livelihoods, and payments for ecosystem services. Each review highlights the current state of knowledge and identifies research priorities, including major challenges and opportunities. We show that while substantial progress is being made across many areas of scientific research, our understanding of specific issues is often dependent on knowledge from other disciplines. Accelerating the acquisition of reliable and contextualized knowledge about the fate of complex pristine and modified ecosystems is partly dependent on our ability to exploit economies of scale in shared resources and technical expertise, recognise and make explicit interconnections and feedbacks among sub-disciplines, increase the temporal and spatial scale of existing studies, and improve the dissemination of scientific findings to policy makers and society at large. Enhancing interaction among research efforts is vital if we are to make the most of limited funds and overcome the challenges posed by addressing large

  15. State of the art applications of social network analysis

    CERN Document Server

    Can, Fazli; Polat, Faruk

    2014-01-01

    Social network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine learning and data mining. This work covers frontier studies on social network analysis and mining from different perspectives such as social network sites, financial data, e-mails, forums, academic research funds, XML technology, blog content, community detection and clique finding, prediction of user

  16. Integration of scientific and social networks

    NARCIS (Netherlands)

    Neshati, Mahmood; Hiemstra, Djoerd; Asgari, Ehsaneddin; Beigy, Hamid

    In this paper, we address the problem of scientific-social network integration to find a matching relationship between members of these networks (i.e. The DBLP publication network and the Twitter social network). This task is a crucial step toward building a multi environment expert finding system

  17. Durer-pentagon-based complex network

    Directory of Open Access Journals (Sweden)

    Rui Hou

    2016-04-01

    Full Text Available A novel Durer-pentagon-based complex network was constructed by adding a centre node. The properties of the complex network including the average degree, clustering coefficient, average path length, and fractal dimension were determined. The proposed complex network is small-world and fractal.

  18. Complex Networks in and beyond Physics

    CERN Document Server

    Volchenkov, D

    2007-01-01

    Physicists study a wide variety of phenomena creating new interdisciplinary research fields by applying theories and methods originally developed in physics in order to solve problems in economics, social science, biology, medicine, technology, etc. In their turn, these different branches of science inspire the invention of new concepts in physics. A basic tool of analysis, in such a context, is the mathematical theory of complexity concerned with the study of complex systems including human economies, climate, nervous systems, cells and living things, including human beings, as well as modern energy or communication infrastructures which are all networks of some kind. Recently, complexity has become a natural domain of interest of the real world socio-cognitive systems, linguistics, and emerging systemics research. The phenomena to be studied and understood arise from neither the physical laws nor the abstraction of mathematics. The challenge is to discern and formulate plausible mathematical structures to d...

  19. Robustness and Optimization of Complex Networks: Reconstructability, Algorithms and Modeling

    NARCIS (Netherlands)

    Liu, D.

    2013-01-01

    The infrastructure networks, including the Internet, telecommunication networks, electrical power grids, transportation networks (road, railway, waterway, and airway networks), gas networks and water networks, are becoming more and more complex. The complex infrastructure networks are crucial to our

  20. Social network models predict movement and connectivity in ecological landscapes

    Science.gov (United States)

    Fletcher, Robert J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, Wiley M.

    2011-01-01

    Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

  1. 基于社会网络分析法的复杂工程项目组织网络模型构建%Research on organizing network model for complex construction project based on social network analysis

    Institute of Scientific and Technical Information of China (English)

    杨琳

    2012-01-01

    从复杂工程项目组织的社会性着手,针对目前项目组织管理和控制在实际应用中出现的问题,研究一种优化项目群组织的有效方法.通过分析复杂工程项目组织结构的网络特性,建立项目组织的优化模型,借助SNA构建组织网络模型,运用UCINET对实例进行定量分析,找到项目组织的关键指标的量化途径.通过模型的构建,可以得出SNA理论是研究工程项目组织关系的有效理论方法,为其组织优化提供了交互视角,有利于组织中关系人目标的实现.%This paper processes from the complex construction organizational,targeted the current project organization and management and control in the practical application problems,studies a method to optimize the effective project organization.This paper points out the organization of control of project management into the field of social network analysis(SNA),aqualitative social network model for construction project organization is established;and then this model is quantitatively analyzed with the help of UCINET.By model building,SNA theory can be drawn to study the relationship between urban complex project organization and effective group theoretical methods,which can fully demonstrate the organization and management in the areas of project feasibility.

  2. Social networks--the future for health care delivery.

    Science.gov (United States)

    Griffiths, Frances; Cave, Jonathan; Boardman, Felicity; Ren, Justin; Pawlikowska, Teresa; Ball, Robin; Clarke, Aileen; Cohen, Alan

    2012-12-01

    With the rapid growth of online social networking for health, health care systems are experiencing an inescapable increase in complexity. This is not necessarily a drawback; self-organising, adaptive networks could become central to future health care delivery. This paper considers whether social networks composed of patients and their social circles can compete with, or complement, professional networks in assembling health-related information of value for improving health and health care. Using the framework of analysis of a two-sided network--patients and providers--with multiple platforms for interaction, we argue that the structure and dynamics of such a network has implications for future health care. Patients are using social networking to access and contribute health information. Among those living with chronic illness and disability and engaging with social networks, there is considerable expertise in assessing, combining and exploiting information. Social networking is providing a new landscape for patients to assemble health information, relatively free from the constraints of traditional health care. However, health information from social networks currently complements traditional sources rather than substituting for them. Networking among health care provider organisations is enabling greater exploitation of health information for health care planning. The platforms of interaction are also changing. Patient-doctor encounters are now more permeable to influence from social networks and professional networks. Diffuse and temporary platforms of interaction enable discourse between patients and professionals, and include platforms controlled by patients. We argue that social networking has the potential to change patterns of health inequalities and access to health care, alter the stability of health care provision and lead to a reformulation of the role of health professionals. Further research is needed to understand how network structure combined with

  3. Multistage Campaigning in Social Networks

    CERN Document Server

    Farajtabar, Mehrdad; Harati, Sahar; Song, Le; Zha, Hongyuan

    2016-01-01

    We consider the problem of how to optimize multi-stage campaigning over social networks. The dynamic programming framework is employed to balance the high present reward and large penalty on low future outcome in the presence of extensive uncertainties. In particular, we establish theoretical foundations of optimal campaigning over social networks where the user activities are modeled as a multivariate Hawkes process, and we derive a time dependent linear relation between the intensity of exogenous events and several commonly used objective functions of campaigning. We further develop a convex dynamic programming framework for determining the optimal intervention policy that prescribes the required level of external drive at each stage for the desired campaigning result. Experiments on both synthetic data and the real-world MemeTracker dataset show that our algorithm can steer the user activities for optimal campaigning much more accurately than baselines.

  4. Googling social interactions: web search engine based social network construction.

    Science.gov (United States)

    Lee, Sang Hoon; Kim, Pan-Jun; Ahn, Yong-Yeol; Jeong, Hawoong

    2010-07-21

    Social network analysis has long been an untiring topic of sociology. However, until the era of information technology, the availability of data, mainly collected by the traditional method of personal survey, was highly limited and prevented large-scale analysis. Recently, the exploding amount of automatically generated data has completely changed the pattern of research. For instance, the enormous amount of data from so-called high-throughput biological experiments has introduced a systematic or network viewpoint to traditional biology. Then, is "high-throughput" sociological data generation possible? Google, which has become one of the most influential symbols of the new Internet paradigm within the last ten years, might provide torrents of data sources for such study in this (now and forthcoming) digital era. We investigate social networks between people by extracting information on the Web and introduce new tools of analysis of such networks in the context of statistical physics of complex systems or socio-physics. As a concrete and illustrative example, the members of the 109th United States Senate are analyzed and it is demonstrated that the methods of construction and analysis are applicable to various other weighted networks.

  5. 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.

  6. Mapping Nuclear Decay to Complex Network

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    Network model is always a key topic in the research of network science. Large Unifying Hybrid Network (LUHNM) theory, which we proposed before, is a universal network model that can be used to depict the diversity and complexity of the natural network.

  7. 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....

  8. Social Networking Sites: A premise on enhancement

    Directory of Open Access Journals (Sweden)

    MANINDERPAL SINGH SAINI

    2013-12-01

    Full Text Available 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 social networking sites toward success. We conclude that the management of social networking sites should be treated as a process that is pragmatic and paradoxically, be stimulated.

  9. 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

  10. 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.

  11. Three lines to view language network. Comment on "Approaching human language with complex networks" by Cong and Liu

    Science.gov (United States)

    Zhao, Yiyi

    2014-12-01

    Language is a kind of complex dynamic network [1-3]. The complexity of language system embodies the interaction and evolution of various languages symbols. The neural network is the physiological basis of language generating and understanding. It also provides a basis to researches on language system by adopting complex network technology and social network analysis. The review [4] gives us three lines to view researches of language network in recent years.

  12. Structural Analysis of Complex Networks

    CERN Document Server

    Dehmer, Matthias

    2011-01-01

    Filling a gap in literature, this self-contained book presents theoretical and application-oriented results that allow for a structural exploration of complex networks. The work focuses not only on classical graph-theoretic methods, but also demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems. Applications to biology, chemistry, linguistics, and data analysis are emphasized. The book is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science,

  13. Mathematical Properties of Complex Networks

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2011-01-01

    Full Text Available Many researchers are attempting to create systems which
    mimic human thought, or understand speech, or beat to the best human chess-player [14]. Understanding intelligence and Creating intelligent artifacts both are the twin goals of Artificial Intelligence (AI.In more recent times, the interest is focused on problems related with Complex Networks [3, 5,6, 19], in particular on questions such as clustering search and identification. We attempt, in this paper, a panoramic vision of such mathematical methods in AI.

  14. Longest-path attacks on complex networks

    CERN Document Server

    Pu, Cunlai

    2014-01-01

    We investigate the longest-path attacks on complex networks. Specifically, we remove approximately the longest simple path from a network iteratively until there are no paths left in the network. We propose two algorithms, the random augmenting approach (RPA) and the Hamilton-path based approach (HPA), for finding the approximately longest simple path in a network. Results demonstrate that steps of longest-path attacks increase with network density linearly for random networks, while exponentially increasing for scale-free networks. The more homogeneous the degree distribution is, the more fragile the network, which is totally different from the previous results of node or edge attacks. HPA is generally more efficient than RPA in the longest-path attacks of complex networks. These findings further help us understand the vulnerability of complex systems, better protect complex systems, and design more tolerant complex systems.

  15. Using Social Network Research in HRM

    DEFF Research Database (Denmark)

    Kaše, Robert; King, Zella; Minbaeva, Dana

    2013-01-01

    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......; 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....

  16. A new information dimension of complex networks

    Energy Technology Data Exchange (ETDEWEB)

    Wei, Daijun [School of Computer and Information Science, Southwest University, Chongqing 400715 (China); School of Science, Hubei University for Nationalities, Enshi 445000 (China); Wei, Bo [School of Computer and Information Science, Southwest University, Chongqing 400715 (China); Hu, Yong [Institute of Business Intelligence and Knowledge Discovery, Guangdong University of Foreign Studies, Guangzhou 510006 (China); Zhang, Haixin [School of Computer and Information Science, Southwest University, Chongqing 400715 (China); Deng, Yong, E-mail: ydeng@swu.edu.cn [School of Computer and Information Science, Southwest University, Chongqing 400715 (China); School of Engineering, Vanderbilt University, TN 37235 (United States)

    2014-03-01

    Highlights: •The proposed measure is more practical than the classical information dimension. •The difference of information for box in the box-covering algorithm is considered. •Results indicate the measure can capture the fractal property of complex networks. -- Abstract: The fractal and self-similarity properties are revealed in many complex networks. The classical information dimension is an important method to study fractal and self-similarity properties of planar networks. However, it is not practical for real complex networks. In this Letter, a new information dimension of complex networks is proposed. The nodes number in each box is considered by using the box-covering algorithm of complex networks. The proposed method is applied to calculate the fractal dimensions of some real networks. Our results show that the proposed method is efficient when dealing with the fractal dimension problem of complex networks.

  17. Topological implications of negative curvature for biological and social networks

    Science.gov (United States)

    Albert, Réka; DasGupta, Bhaskar; Mobasheri, Nasim

    2014-03-01

    Network measures that reflect the most salient properties of complex large-scale networks are in high demand in the network research community. In this paper we adapt a combinatorial measure of negative curvature (also called hyperbolicity) to parametrized finite networks, and show that a variety of biological and social networks are hyperbolic. This hyperbolicity property has strong implications on the higher-order connectivity and other topological properties of these networks. Specifically, we derive and prove bounds on the distance among shortest or approximately shortest paths in hyperbolic networks. We describe two implications of these bounds to crosstalk in biological networks, and to the existence of central, influential neighborhoods in both biological and social networks.

  18. Brain and Social Networks: Fundamental Building Blocks of Human Experience.

    Science.gov (United States)

    Falk, Emily B; Bassett, Danielle S

    2017-09-01

    How do brains shape social networks, and how do social ties shape the brain? Social networks are complex webs by which ideas spread among people. Brains comprise webs by which information is processed and transmitted among neural units. While brain activity and structure offer biological mechanisms for human behaviors, social networks offer external inducers or modulators of those behaviors. Together, these two axes represent fundamental contributors to human experience. Integrating foundational knowledge from social and developmental psychology and sociology on how individuals function within dyads, groups, and societies with recent advances in network neuroscience can offer new insights into both domains. Here, we use the example of how ideas and behaviors spread to illustrate the potential of multilayer network models. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Detecting Change in Longitudinal Social Networks

    Science.gov (United States)

    2011-01-01

    marketing campaigns and media on social behavior. Initial Construct populations, social and knowledge networks, can be hypothetical or real (Carley...patent data bases, phone-networks, email- based-networks, social- media networks and more. Page 6 of 37 Current methods of change detection in...CUSUM C Sta measured fo o be successf Average Bet ct either incre or each socia g increases in the data for fective for ch ork. tistic Over Tim

  20. Analyzing negative ties in social networks

    OpenAIRE

    Mankirat Kaur; Sarbjeet Singh

    2016-01-01

    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 i...

  1. 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

  2. Matching Community Structure Across Online Social Networks

    OpenAIRE

    Lin LI; Campbell, W. M.

    2016-01-01

    The discovery of community structure in networks is a problem of considerable interest in recent years. In online social networks, often times, users are simultaneously involved in multiple social media sites, some of which share common social relationships. It is of great interest to uncover a shared community structure across these networks. However, in reality, users typically identify themselves with different usernames across social media sites. This creates a great difficulty in detecti...

  3. Predicting Group Evolution in the Social Network

    OpenAIRE

    Bródka, Piotr; Kazienko, Przemysław; Kołoszczyk, Bartosz

    2012-01-01

    Groups - social communities are important components of entire societies, analysed by means of the social network concept. Their immanent feature is continuous evolution over time. If we know how groups in the social network has evolved we can use this information and try to predict the next step in the given group evolution. In the paper, a new aproach for group evolution prediction is presented and examined. Experimental studies on four evolving social networks revealed that (i) the predict...

  4. Minimum complexity echo state network.

    Science.gov (United States)

    Rodan, Ali; Tino, Peter

    2011-01-01

    Reservoir computing (RC) refers to a new class of state-space models with a fixed state transition structure (the reservoir) and an adaptable readout form the state space. The reservoir is supposed to be sufficiently complex so as to capture a large number of features of the input stream that can be exploited by the reservoir-to-output readout mapping. The field of RC has been growing rapidly with many successful applications. However, RC has been criticized for not being principled enough. Reservoir construction is largely driven by a series of randomized model-building stages, with both researchers and practitioners having to rely on a series of trials and errors. To initialize a systematic study of the field, we concentrate on one of the most popular classes of RC methods, namely echo state network, and ask: What is the minimal complexity of reservoir construction for obtaining competitive models and what is the memory capacity (MC) of such simplified reservoirs? On a number of widely used time series benchmarks of different origin and characteristics, as well as by conducting a theoretical analysis we show that a simple deterministically constructed cycle reservoir is comparable to the standard echo state network methodology. The (short-term) MC of linear cyclic reservoirs can be made arbitrarily close to the proved optimal value.

  5. Community evolution mining and analysis in social network

    Science.gov (United States)

    Liu, Hongtao; Tian, Yuan; Liu, Xueyan; Jian, Jie

    2017-03-01

    With the development of digital and network technology, various social platforms emerge. These social platforms have greatly facilitated access to information, attracting more and more users. They use these social platforms every day to work, study and communicate, so every moment social platforms are generating massive amounts of data. These data can often be modeled as complex networks, making large-scale social network analysis possible. In this paper, the existing evolution classification model of community has been improved based on community evolution relationship over time in dynamic social network, and the Evolution-Tree structure is proposed which can show the whole life cycle of the community more clearly. The comparative test result shows that the improved model can excavate the evolution relationship of the community well.

  6. Social networks as journalistic paradigm

    Directory of Open Access Journals (Sweden)

    José Manuel Noguera Vivo, Ph. D

    2010-01-01

    Full Text Available Spain is one of the countries with higher use of social networks in the world. Among them, Facebook is emerging as one of the most significant internationally. If these phenomena are combined with the current transformation of journalism, it is not surprising that some Spanish cybermedia have approached this platform to develop new products for the Web. From this starting point, this article focuses on the recent performances of Spanish cybermedia within social networks, specifically Facebook, with an exploratory study about both the use of native media of Web and media from the print newspapers. This research studies the use of most important Spanish cybermedia from a structured observation. Data are collected through a content analysis with an ad hoc questionnaire. The results point out few cybermedia which seem to take advantage of these networks in terms of participation. This allows us to conclude that we are in a young state of relations on the Web, where spaces and resources are not optimized.

  7. Synchronizability on complex networks via pinning control

    Indian Academy of Sciences (India)

    Yi Liang; Xingyuan Wang

    2013-04-01

    It is proved that the maximum eigenvalue sequence of the principal submatrices of coupling matrix is decreasing. The method of calculating the number of pinning nodes is given based on this theory. The findings reveal the relationship between the decreasing speed of maximum eigenvalue sequence of the principal submatrices for coupling matrix and the synchronizability on complex networks via pinning control. We discuss the synchronizability on some networks, such as scale-free networks and small-world networks. Numerical simulations show that different pinning strategies have different pinning synchronizability on the same complex network, and the synchronizability with pinning control is consistent with one without pinning control in various complex networks.

  8. 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.

  9. Opinion control in complex networks

    Science.gov (United States)

    Masuda, Naoki

    2015-03-01

    In many political elections, the electorate appears to be a composite of partisan and independent voters. Given that partisans are not likely to convert to a different party, an important goal for a political party could be to mobilize independent voters toward the party with the help of strong leadership, mass media, partisans, and the effects of peer-to-peer influence. Based on the exact solution of classical voter model dynamics in the presence of perfectly partisan voters (i.e., zealots), we propose a computational method that uses pinning control strategy to maximize the share of a party in a social network of independent voters. The party, corresponding to the controller or zealots, optimizes the nodes to be controlled given the information about the connectivity of independent voters and the set of nodes that the opposing party controls. We show that controlling hubs is generally a good strategy, but the optimized strategy is even better. The superiority of the optimized strategy is particularly eminent when the independent voters are connected as directed (rather than undirected) networks.

  10. Evolving Social Networks via Friend Recommendations

    OpenAIRE

    Verma, Amit Kumar; Pal, Manjish

    2015-01-01

    A social network grows over a period of time with the formation of new connections and relations. In recent years we have witnessed a massive growth of online social networks like Facebook, Twitter etc. So it has become a problem of extreme importance to know the destiny of these networks. Thus predicting the evolution of a social network is a question of extreme importance. A good model for evolution of a social network can help in understanding the properties responsible for the changes occ...

  11. Location Privacy Protection on Social Networks

    Science.gov (United States)

    Zhan, Justin; Fang, Xing

    Location information is considered as private in many scenarios. Protecting location information on mobile ad-hoc networks has attracted much research in past years. However, location information protection on social networks has not been paid much attention. In this paper, we present a novel location privacy protection approach on the basis of user messages in social networks. Our approach grants flexibility to users by offering them multiple protecting options. To the best of our knowledge, this is the first attempt to protect social network users' location information via text messages. We propose five algorithms for location privacy protection on social networks.

  12. 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…

  13. 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…

  14. Understanding Decision Making through Complexity in Professional Networks

    Directory of Open Access Journals (Sweden)

    Kon Shing Kenneth Chung

    2014-01-01

    Full Text Available The attitudes of general practitioners (GP play an influential role in their decision making about patient treatment and care. Considering the GP-patient encounter as a complex system, the interactions between the GP and their personal network of peers give rise to “aggregate complexity,” which in turn influences the GP’s decisions about patient treatment. This study models aggregate complexity and its influence in decision making in primary care through the use of social network metrics. Professional network and attitudinal data on decision making responsibility from 107 rural GPs were analysed. Social network measures of “density” and “inclusiveness” were used for computing the “interrelatedness” of components within such a “complex system.” The “number of components” and “degree of interrelatedness” were used to determine the complexity profiles, which was then used to associate with responsibility in decision making for each GP. GPs in simple profiles (i.e., with low components and interactions in contrast to those in nonsimple profiles, indicate a higher responsibility for the decisions they make in medical care. This study suggests that social networks-based complexity profiles are useful for understanding decision making in primary care as it accounts for the role of influence through the professional networks of GPs.

  15. Mobile Social Network in a Cultural Context

    DEFF Research Database (Denmark)

    Liu, Jun

    2010-01-01

    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...... contributes to the explosive growth of the message within mobile social networks under special circumstances, such as during festivals and holidays and social disturbances. This circulation in turn increases both the dissemination and credibility of messages, and rumours. The characteristics and strength...

  16. Optimization Techniques for Analysis of Biological and Social Networks

    Science.gov (United States)

    2012-03-28

    systematic fashion under a unifying theoretical and algorithmic framework . Optimization, Complex Networks, Social Network Analysis, Computational...analyzing a new metaheuristic technique, variable objective search. 3. Experimentation and application: Implement the proposed algorithms, test and fine...exact solutions are presented. In [3], we introduce the variable objective search framework for combinatorial optimization. The method utilizes

  17. 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...

  18. A Computer Network for Social Scientists.

    Science.gov (United States)

    Gerber, Barry

    1989-01-01

    Describes a microcomputer-based network developed at the University of California Los Angeles to support education in the social sciences. Topics discussed include technological, managerial, and academic considerations of university networking; the use of the network in teaching macroeconomics, social demographics, and symbolic logic; and possible…

  19. Computational social networks security and privacy

    CERN Document Server

    2012-01-01

    Presents the latest advances in security and privacy issues in computational social networks, and illustrates how both organizations and individuals can be protected from real-world threats Discusses the design and use of a wide range of computational tools and software for social network analysis Provides experience reports, survey articles, and intelligence techniques and theories relating to specific problems in network technology

  20. Multiplex social ecological network analysis reveals how social changes affect community robustness more than resource depletion.

    Science.gov (United States)

    Baggio, Jacopo A; BurnSilver, Shauna B; Arenas, Alex; Magdanz, James S; Kofinas, Gary P; De Domenico, Manlio

    2016-11-29

    Network analysis provides a powerful tool to analyze complex influences of social and ecological structures on community and household dynamics. Most network studies of social-ecological systems use simple, undirected, unweighted networks. We analyze multiplex, directed, and weighted networks of subsistence food flows collected in three small indigenous communities in Arctic Alaska potentially facing substantial economic and ecological changes. Our analysis of plausible future scenarios suggests that changes to social relations and key households have greater effects on community robustness than changes to specific wild food resources.

  1. An evolutionary model of social networks

    Science.gov (United States)

    Ludwig, M.; Abell, P.

    2007-07-01

    Social networks in communities, markets, and societies self-organise through the interactions of many individuals. In this paper we use a well-known mechanism of social interactions — the balance of sentiment in triadic relations — to describe the development of social networks. Our model contrasts with many existing network models, in that people not only establish but also break up relations whilst the network evolves. The procedure generates several interesting network features such as a variety of degree distributions and degree correlations. The resulting network converges under certain conditions to a steady critical state where temporal disruptions in triangles follow a power-law distribution.

  2. Trust transitivity in social networks

    CERN Document Server

    Richters, Oliver

    2010-01-01

    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 degree distribution, 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 author...

  3. Emergence of communities and diversity in social networks

    Science.gov (United States)

    Han, Xiao; Cao, Shinan; Shen, Zhesi; Zhang, Boyu; Wang, Wen-Xu; Cressman, Ross

    2017-01-01

    Communities are common in complex networks and play a significant role in the functioning of social, biological, economic, and technological systems. Despite widespread interest in detecting community structures in complex networks and exploring the effect of communities on collective dynamics, a deep understanding of the emergence and prevalence of communities in social networks is still lacking. Addressing this fundamental problem is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in society. An elusive question is how communities with common internal properties arise in social networks with great individual diversity. Here, we answer this question using the ultimatum game, which has been a paradigm for characterizing altruism and fairness. We experimentally show that stable local communities with different internal agreements emerge spontaneously and induce social diversity into networks, which is in sharp contrast to populations with random interactions. Diverse communities and social norms come from the interaction between responders with inherent heterogeneous demands and rational proposers via local connections, where the former eventually become the community leaders. This result indicates that networks are significant in the emergence and stabilization of communities and social diversity. Our experimental results also provide valuable information about strategies for developing network models and theories of evolutionary games and social dynamics. PMID:28235785

  4. Emergence of communities and diversity in social networks.

    Science.gov (United States)

    Han, Xiao; Cao, Shinan; Shen, Zhesi; Zhang, Boyu; Wang, Wen-Xu; Cressman, Ross; Stanley, H Eugene

    2017-03-14

    Communities are common in complex networks and play a significant role in the functioning of social, biological, economic, and technological systems. Despite widespread interest in detecting community structures in complex networks and exploring the effect of communities on collective dynamics, a deep understanding of the emergence and prevalence of communities in social networks is still lacking. Addressing this fundamental problem is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in society. An elusive question is how communities with common internal properties arise in social networks with great individual diversity. Here, we answer this question using the ultimatum game, which has been a paradigm for characterizing altruism and fairness. We experimentally show that stable local communities with different internal agreements emerge spontaneously and induce social diversity into networks, which is in sharp contrast to populations with random interactions. Diverse communities and social norms come from the interaction between responders with inherent heterogeneous demands and rational proposers via local connections, where the former eventually become the community leaders. This result indicates that networks are significant in the emergence and stabilization of communities and social diversity. Our experimental results also provide valuable information about strategies for developing network models and theories of evolutionary games and social dynamics.

  5. 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).

  6. Spatio-temporal keyword queries in social networks

    DEFF Research Database (Denmark)

    Cozza, V.; Messina, Alessandro; Montesi, D.

    2013-01-01

    Due to the large amount of social network data produced at an ever growing speed and their complex nature, recent works have addressed the problem of efficiently querying such data according to social, temporal or spatial dimensions. In this work we propose a data model that keeps into account all...

  7. Complexity Characteristics of Currency Networks

    Science.gov (United States)

    Gorski, A. Z.; Drozdz, S.; Kwapien, J.; Oswiecimka, P.

    2006-11-01

    A large set of daily FOREX time series is analyzed. The corresponding correlation matrices (CM) are constructed for USD, EUR and PLN used as the base currencies. The triangle rule is interpreted as constraints reducing the number of independent returns. The CM spectrum is computed and compared with the cases of shuffled currencies and a fictitious random currency taken as a base currency. The Minimal Spanning Tree (MST) graphs are calculated and the clustering effects for strong currencies are found. It is shown that for MSTs the node rank has power like, scale free behavior. Finally, the scaling exponents are evaluated and found in the range analogous to those identified recently for various complex networks.

  8. Community structure of complex networks based on continuous neural network

    Science.gov (United States)

    Dai, Ting-ting; Shan, Chang-ji; Dong, Yan-shou

    2017-09-01

    As a new subject, the research of complex networks has attracted the attention of researchers from different disciplines. Community structure is one of the key structures of complex networks, so it is a very important task to analyze the community structure of complex networks accurately. In this paper, we study the problem of extracting the community structure of complex networks, and propose a continuous neural network (CNN) algorithm. It is proved that for any given initial value, the continuous neural network algorithm converges to the eigenvector of the maximum eigenvalue of the network modularity matrix. Therefore, according to the stability of the evolution of the network symbol will be able to get two community structure.

  9. Networked Learning in Networks: infrastructures for social learning & distributed innovation

    NARCIS (Netherlands)

    Sloep, Peter

    2011-01-01

    Sloep, P. B. (2011, 1-3 September). Networked Learning in Networks: infrastructures for social learning & distributed innovation. Presentation at the Third International Conference on Software, Services and Semantic Technologies (S3T 2011), Bourgas, Bulgaria.

  10. 复杂网络结构范型下的社会治理协同创新%Synergetic Innovation in Social Governance in a Complex Network Structural Paradigm

    Institute of Scientific and Technical Information of China (English)

    范如国; Tan Yuehan; Gong Huayan

    2016-01-01

    社会本质上是一个开放演化、具有耦合作用和适应性的复杂网络系统,社会治理是一项庞大而又复杂的系统工程.由于环境和社会事物的复杂性和不确定性,由政府主导的传统管理模式不能对复杂社会问题给出有效的解释和应对,有必要引入复杂科学范式.复杂科学尤其是复杂系统理论与社会治理具有内在的契合性,它能够揭示社会治理复杂性产生的内在机理及其规律.复杂系统理论表明,越是复杂的系统,系统协调的要求也越高,协同效应也就越显著.复杂社会网络系统所具有的小世界、无标度、社团结构、偏好连接及虚实“二相”性拓扑结构对社会治理有着直接而深刻的影响.加强和创新社会治理需要分析社会系统的复杂网络结构及其特征,建立社会治理的协同创新机制,展开协同社会治理.%Society is in essence a complex network system that is open,evolving and adaptable and possesses a coupling function.Social governance is a large-scale and complex systems engineering project.Due to the complexity and uncertainty of the environment and social affairs,the traditional government-led linear management model cannot provide effective interpretations and responses to complex social issues,and it is thus necessary to introduce the complexity scientific paradigm.Complexity science,especially complex system theory,has an intrinsic correspondence with social governance,and can reveal the inherent occurrence mechanism and rules brought about by the complexity of social governance.It indicates that the more complex a system is,the greater will be its requirements for systemic coordination and the more apparent its synergetic effects.A complex social network system is small-world and scale-free,with a community structure,preferential attachment and a topological structure characterized by the duality of virtuality and actuality.All of these have a direct and profound effect

  11. Socioecological regime shifts in the setting of complex social interactions

    Science.gov (United States)

    Sugiarto, Hendrik Santoso; Chung, Ning Ning; Lai, Choy Heng; Chew, Lock Yue

    2015-06-01

    The coupling between social and ecological system has become more ubiquitous and predominant in the current era. The strong interaction between these systems can bring about regime shifts which in the extreme can lead to the collapse of social cooperation and the extinction of ecological resources. In this paper, we study the occurrence of such regime shifts in the context of a coupled social-ecological system where social cooperation is established by means of sanction that punishes local selfish act and promotes norms that prescribe nonexcessive resource extraction. In particular, we investigate the role of social networks on social-ecological regimes shift and the corresponding hysteresis effects caused by the local ostracism mechanism under different social and ecological parameters. Our results show that a lowering of network degree reduces the hysteresis effect and also alters the tipping point, which is duly verified by our numerical results and analytical estimation. Interestingly, the hysteresis effect is found to be stronger in scale-free network in comparison with random network even when both networks have the same average degree. These results provide deeper insights into the resilience of these systems, and can have important implications on the management of coupled social-ecological systems with complex social interactions.

  12. Outer Synchronization of Complex Networks by Impulse

    Institute of Scientific and Technical Information of China (English)

    孙文; 燕子宗; 陈士华; 吕金虎

    2011-01-01

    This paper investigates outer synchronization of complex networks, especially, outer complete synchronization and outer anti-synchronization between the driving network and the response network. Employing the impulsive control method which is uncontinuous, simple, efficient, low-cost and easy to implement in practical applications, we obtain some sufficient conditions of outer complete synchronization and outer anti-synchronization between two complex networks. Numerical simulations demonstrate the effectiveness of the proposed impulsive control scheme.

  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. Matching Community Structure Across Online Social Networks

    CERN Document Server

    Li, Lin

    2016-01-01

    The discovery of community structure in networks is a problem of considerable interest in recent years. In online social networks, often times, users are simultaneously involved in multiple social media sites, some of which share common social relationships. It is of great interest to uncover a shared community structure across these networks. However, in reality, users typically identify themselves with different usernames across social media sites. This creates a great difficulty in detecting the community structure. In this paper, we explore several approaches for community detection across online social networks with limited knowledge of username alignment across the networks. We refer to the known alignment of usernames as seeds. We investigate strategies for seed selection and its impact on networks with a different fraction of overlapping vertices. The goal is to study the interplay between network topologies and seed selection strategies, and to understand how it affects the detected community structu...

  15. CONNECTIONS USING SOCIAL NETWORKS AND SOCIAL INTELLIGENCE OF STUDENTS

    Directory of Open Access Journals (Sweden)

    Belma Duvnjak

    2013-05-01

    Full Text Available Social intelligence is the ability and skills to cope with everyday life situations and how to cope with interpersonal relationships. Today's generation of relationships based, carried and nurtured through various social networks. The aim of the presented research is to identify the impact of social networks on the development of social intelligence. The study was done on a sample, which makes the 208 students from the Faculty of Education at the University "Džemal Bijedić" in Mostar. The results show that the impact of social networks on the development of positive social intelligence. Greater achievement on tests of social intelligence (SI were significantly correlated with the amount of time spent using different social networks.

  16. How random are complex networks

    CERN Document Server

    Orsini, Chiara; Jamakovic, Almerima; Mahadevan, Priya; Colomer-de-Simón, Pol; Vahdat, Amin; Bassler, Kevin E; Toroczkai, Zoltán; Boguñá, Marián; Caldarelli, Guido; Fortunato, Santo; Krioukov, Dmitri

    2015-01-01

    Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the $dk$-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks---the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain---and find that many important local and global structural properties of these networks are closely reproduced by $dk$-random graphs whose degree distributions, degree correlations, and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness.

  17. Social networks in borderline personality disorder.

    Science.gov (United States)

    Clifton, Allan; Pilkonis, Paul A; McCarty, Christopher

    2007-08-01

    The interpersonal dysfunction that characterizes borderline personality disorder (BPD) has generally been studied using broad global measures, leading to a lack of precision. We report on a novel methodology using social network analysis (SNA) to quantify interactions with others in the patient's social world. We assessed the social networks of 22 clinical patients, diagnosed with either BPD (N = 11) or no personality disorder (No PD; N = 11). The social networks of patients with BPD contained a greater number of former romantic partners, and a greater number of relationships that had been terminated. Mixed model analyses found that the No PD group reported higher levels of positive relationships (e.g., trust, social support) with more central members of their social networks, whereas the BPD group did not discriminate among members of their networks. Results suggest deficits in social cognition for positive relations, but not for negative relations such as interpersonal conflict.

  18. A User Perspective on Social Networking Sites

    DEFF Research Database (Denmark)

    Sørensen, Lene Tolstrup; Porras, Jari; Hajikhani, Arash

    2014-01-01

    For years, social media have been a part of daily life. Within the last 5-10 years, the use of social media (and in particular social networking sites) has expanded to almost all sides of life: private people, businesses and public institutions. This paper presents an overview of different uses...... of social networks to give a picture of the variety in use. The paper describes differences in private persons’ use of social networking sites, different business purposes, and how social networking sites can challenge public administrations. Throughout the paper there are provided small cases...... and situations where the social networking sites have been used in a remarkable way. The paper is made in collaboration between partners in the World Wide Research Forum....

  19. Role of Security in Social Networking

    Directory of Open Access Journals (Sweden)

    David Hiatt

    2016-02-01

    Full Text Available In this paper, the concept of security and privacy in social media, or social networking will be discussed. First, a brief history and the concept of social networking will be introduced. Many of the security risks associated with using social media are presented. Also, the issue of privacy and how it relates to security are described. Based on these discussions, some solutions to improve a user’s privacy and security on social networks will be suggested. Our research will help the readers to understand the security and privacy issues for the social network users, and some steps which can be taken by both users and social network organizations to help improve security and privacy.

  20. A User Perspective on Social Networking Sites

    DEFF Research Database (Denmark)

    Sørensen, Lene Tolstrup; Porras, Jari; Hajikhani, Arash

    2014-01-01

    For years, social media have been a part of daily life. Within the last 5-10 years, the use of social media (and in particular social networking sites) has expanded to almost all sides of life: private people, businesses and public institutions. This paper presents an overview of different uses...... of social networks to give a picture of the variety in use. The paper describes differences in private persons’ use of social networking sites, different business purposes, and how social networking sites can challenge public administrations. Throughout the paper there are provided small cases...... and situations where the social networking sites have been used in a remarkable way. The paper is made in collaboration between partners in the World Wide Research Forum....

  1. Optimising the topology of complex neural networks

    CERN Document Server

    Jiang, Fei; Schoenauer, Marc

    2007-01-01

    In this paper, we study instances of complex neural networks, i.e. neural netwo rks with complex topologies. We use Self-Organizing Map neural networks whose n eighbourhood relationships are defined by a complex network, to classify handwr itten digits. We show that topology has a small impact on performance and robus tness to neuron failures, at least at long learning times. Performance may howe ver be increased (by almost 10%) by artificial evolution of the network topo logy. In our experimental conditions, the evolved networks are more random than their parents, but display a more heterogeneous degree distribution.

  2. SOCIAL NETWORK EFFECTS ON ROMANTIC RELATIONSHIP

    OpenAIRE

    Can, Fatma; Selim HOVARDAOGLU

    2015-01-01

    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 app...

  3. 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...comScore, GlobalWebIndex, Alexa, and financial reports for the parent companies of the social networking tools. The subsequent list includes global... company websites and financial reports. LinkedIn does not provide a monthly active user number, but it reports 300 million regis- tered users. Because

  4. Discovering Mobile Social Networks by Semantic Technologies

    Science.gov (United States)

    Jung, Jason J.; Choi, Kwang Sun; Park, Sung Hyuk

    It has been important for telecommunication companies to discover social networks from mobile subscribers. They have attempted to provide a number of recommendation services, but they realized that the services were not successful. In this chapter, we present semantic technologies for discovering social networks. The process is mainly composed of two steps; (1) profile identification and (2) context understanding. Through developing a Next generation Contents dElivery (NICE) platform, we were able to generate various services based on the discovered social networks.

  5. Group Evolution Discovery in Social Networks

    OpenAIRE

    Bródka, Piotr; Saganowski, Stanisław; Kazienko, Przemysław

    2013-01-01

    Group extraction and their evolution are among the topics which arouse the greatest interest in the domain of social network analysis. However, while the grouping methods in social networks are developed very dynamically, the methods of group evolution discovery and analysis are still uncharted territory on the social network analysis map. Therefore the new method for the group evolution discovery called GED is proposed in this paper. Additionally, the results of the first experiments on the ...

  6. A Dynamic Algebraic Specification for Social Networks

    CERN Document Server

    Ksystra, Katerina; Triantafyllou, Nikolaos; Stefaneas, Petros

    2011-01-01

    With the help of the Internet, social networks have grown rapidly. This has increased security requirements. We present a formalization of social networks as composite behavioral objects, defined using the Observational Transition System (OTS) approach. Our definition is then translated to the OTS/CafeOBJ algebraic specification methodology. This translation allows the formal verification of safety properties for social networks via the Proof Score method. Finally, using this methodology we formally verify some security properties.

  7. The Strategic Paradox of Social Networks

    Science.gov (United States)

    2011-03-18

    cause long-lasting effects. For example, a recent Career Builder survey found the number of civilian employers who used social networking sites as...Service members discussing political subjects on social networking sites can quickly attract negative attention. In March 2010, Marine Corps Sergeant...on social networking sites . In March 2010, stories surfaced reporting the Israeli army canceled a mission after a soldier “disclosed the name of the

  8. 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.

  9. Common neighbour structure and similarity intensity in complex networks

    Science.gov (United States)

    Hou, Lei; Liu, Kecheng

    2017-10-01

    Complex systems as networks always exhibit strong regularities, implying underlying mechanisms governing their evolution. In addition to the degree preference, the similarity has been argued to be another driver for networks. Assuming a network is randomly organised without similarity preference, the present paper studies the expected number of common neighbours between vertices. A symmetrical similarity index is accordingly developed by removing such expected number from the observed common neighbours. The developed index can not only describe the similarities between vertices, but also the dissimilarities. We further apply the proposed index to measure of the influence of similarity on the wring patterns of networks. Fifteen empirical networks as well as artificial networks are examined in terms of similarity intensity and degree heterogeneity. Results on real networks indicate that, social networks are strongly governed by the similarity as well as the degree preference, while the biological networks and infrastructure networks show no apparent similarity governance. Particularly, classical network models, such as the Barabási-Albert model, the Erdös-Rényi model and the Ring Lattice, cannot well describe the social networks in terms of the degree heterogeneity and similarity intensity. The findings may shed some light on the modelling and link prediction of different classes of networks.

  10. 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.

  11. Synchronization of fractional order complex dynamical networks

    Science.gov (United States)

    Wang, Yu; Li, Tianzeng

    2015-06-01

    In this letter the synchronization of complex dynamical networks with fractional order chaotic nodes is studied. A fractional order controller for synchronization of complex network is presented. Some new sufficient synchronization criteria are proposed based on the Lyapunov stability theory and the LaSalle invariance principle. These synchronization criteria can apply to an arbitrary fractional order complex network in which the coupling-configuration matrix and the inner-coupling matrix are not assumed to be symmetric or irreducible. It means that this method is more general and effective. Numerical simulations of two fractional order complex networks demonstrate the universality and the effectiveness of the proposed method.

  12. Complex-network description of seismicity

    Directory of Open Access Journals (Sweden)

    S. Abe

    2006-01-01

    Full Text Available The seismic data taken in California and Japan are mapped to growing random networks. It is shown in the undirected network picture that these earthquake networks are scale-free and small-work networks with the power-law connectivity distributions, the large values of the clustering coefficient, and the small values of the average path length. It is demonstrated how the present network approach reveals complexity of seismicity in a novel manner.

  13. 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

  14. Individual Differences as Predictors of Social Networking

    National Research Council Canada - National Science Library

    Orchard, Lisa J; Fullwood, Chris; Galbraith, Niall; Morris, Neil

    2014-01-01

    Research suggests that personality dictates specific Internet preferences. One area that remains relatively unexplored is the influence of personality on engagement with social networking sites ( SNSs...

  15. 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

  16. The Social Side of Information Networking.

    Science.gov (United States)

    Katz, James E.

    1997-01-01

    Explores the social issues, including manners, security, crime (fraud), and social control associated with information networking, with emphasis on the Internet. Also addresses the influence of cellular phones, the Internet and other information technologies on society. (GR)

  17. 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

  18. Dynamics of Complex Interconnected Systems: Networks and Bioprocesses

    CERN Document Server

    Skjeltorp, Arne T

    2006-01-01

    The book reviews the synergism between various fields of research that are confronted with networks, such as genetic and metabolic networks, social networks, the Internet and ecological systems. In many cases, the interacting networks manifest so-called emergent properties that are not possessed by any of the individual components. This means that the detailed knowledge of the components is insufficient to describe the whole system. Recent work has indicated that networks in nature have so-called scale-free characteristics, and the associated dynamic network modelling shows unexpected results such as an amazing robustness against accidental failures. Modelling the signal transduction networks in bioprocesses as in living cells is a challenging interdisciplinary research area. It is now realized that the many features of molecular interaction networks within a cell are shared to a large degree by the other complex systems mentioned above, such as the Internet, computer chips and society. Thus knowledge gained ...

  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. Online community detection for large complex networks.

    Directory of Open Access Journals (Sweden)

    Gang Pan

    Full Text Available Complex networks describe a wide range of systems in nature and society. To understand complex networks, it is crucial to investigate their community structure. In this paper, we develop an online community detection algorithm with linear time complexity for large complex networks. Our algorithm processes a network edge by edge in the order that the network is fed to the algorithm. If a new edge is added, it just updates the existing community structure in constant time, and does not need to re-compute the whole network. Therefore, it can efficiently process large networks in real time. Our algorithm optimizes expected modularity instead of modularity at each step to avoid poor performance. The experiments are carried out using 11 public data sets, and are measured by two criteria, modularity and NMI (Normalized Mutual Information. The results show that our algorithm's running time is less than the commonly used Louvain algorithm while it gives competitive performance.

  1. Structural Dissection for Controlling Complex Networks

    CERN Document Server

    Wang, Wen-Xu; Zhao, Chen; Liu, Yang-Yu; Lai, Ying-Cheng

    2015-01-01

    Controlling complex networked systems has been a central goal in different fields and understanding controllability of complex networks has been at the forefront of contemporary science. Despite the recent progress in the development of controllability theories for complex networks, we continue to lack efficient tools to fully understand the effect of network topology and interaction strengths among nodes on controllability. Here we establish a framework to discern the significance of links and nodes for controlling general complex networks in a simple way based on local information. A dissection process is offered by the framework to probe and classify nodes and links completely, giving rise to a criterion for strong structural controllability. Analytical results indicate phase transitions associated with link and node categories, and strong structural controllability. Applying the tools to real networks demonstrate that real technological networks are strong structurally controllable, whereas most of real s...

  2. Opinion control in complex networks

    CERN Document Server

    Masuda, Naoki

    2014-01-01

    In many instances of election, the electorate appears to be a composite of partisan and independent voters. Given that partisans are not likely to convert to a different party, a main goal for a party could be to mobilize independent voters toward the party with the help of strong leadership, mass media, partisans, and effects of peer-to-peer influence. Based on the exact solution of the classical voter model dynamics in the presence of perfectly partisan voters (i.e., zealots), we propose a computational method to maximize the share of the party in a social network of independent voters by pinning control strategy. The party, corresponding to the controller or zealots, optimizes the nodes to be controlled given the information about the connectivity of independent voters and the set of nodes that the opponent party controls. We show that controlling hubs is generally a good strategy, whereas the optimized strategy is even better. The superiority of the optimized strategy is particularly eminent when the inde...

  3. Competition between global and local online social networks.

    Science.gov (United States)

    Kleineberg, Kaj-Kolja; Boguñá, Marián

    2016-04-27

    The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

  4. Competition between global and local online social networks

    Science.gov (United States)

    Kleineberg, Kaj-Kolja; Boguñá, Marián

    2016-04-01

    The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

  5. How Many "Friends" Do You Need? Teaching Students How to Network Using Social Media

    Science.gov (United States)

    Sacks, Michael Alan; Graves, Nikki

    2012-01-01

    Student reliance on social media is undeniable. However, while we largely regard social media as a new phenomena, the concepts underlying it come directly from social network theory in sociology and organizational behavior. In this article, the authors examine how the social network concepts of size, quality, complexity, diffusion, and distance…

  6. How Many "Friends" Do You Need? Teaching Students How to Network Using Social Media

    Science.gov (United States)

    Sacks, Michael Alan; Graves, Nikki

    2012-01-01

    Student reliance on social media is undeniable. However, while we largely regard social media as a new phenomena, the concepts underlying it come directly from social network theory in sociology and organizational behavior. In this article, the authors examine how the social network concepts of size, quality, complexity, diffusion, and distance…

  7. Dynamical complexity in the perception-based network formation model

    Science.gov (United States)

    Jo, Hang-Hyun; Moon, Eunyoung

    2016-12-01

    Many link formation mechanisms for the evolution of social networks have been successful to reproduce various empirical findings in social networks. However, they have largely ignored the fact that individuals make decisions on whether to create links to other individuals based on cost and benefit of linking, and the fact that individuals may use perception of the network in their decision making. In this paper, we study the evolution of social networks in terms of perception-based strategic link formation. Here each individual has her own perception of the actual network, and uses it to decide whether to create a link to another individual. An individual with the least perception accuracy can benefit from updating her perception using that of the most accurate individual via a new link. This benefit is compared to the cost of linking in decision making. Once a new link is created, it affects the accuracies of other individuals' perceptions, leading to a further evolution of the actual network. As for initial actual networks, we consider both homogeneous and heterogeneous cases. The homogeneous initial actual network is modeled by Erdős-Rényi (ER) random networks, while we take a star network for the heterogeneous case. In any cases, individual perceptions of the actual network are modeled by ER random networks with controllable linking probability. Then the stable link density of the actual network is found to show discontinuous transitions or jumps according to the cost of linking. As the number of jumps is the consequence of the dynamical complexity, we discuss the effect of initial conditions on the number of jumps to find that the dynamical complexity strongly depends on how much individuals initially overestimate or underestimate the link density of the actual network. For the heterogeneous case, the role of the highly connected individual as an information spreader is also discussed.

  8. Threshold learning dynamics in social networks.

    Directory of Open Access Journals (Sweden)

    Juan Carlos González-Avella

    Full Text Available Social learning is defined as the ability of a population to aggregate information, a process which must crucially depend on the mechanisms of social interaction. Consumers choosing which product to buy, or voters deciding which option to take with respect to an important issue, typically confront external signals to the information gathered from their contacts. Economic models typically predict that correct social learning occurs in large populations unless some individuals display unbounded influence. We challenge this conclusion by showing that an intuitive threshold process of individual adjustment does not always lead to such social learning. We find, specifically, that three generic regimes exist separated by sharp discontinuous transitions. And only in one of them, where the threshold is within a suitable intermediate range, the population learns the correct information. In the other two, where the threshold is either too high or too low, the system either freezes or enters into persistent flux, respectively. These regimes are generally observed in different social networks (both complex or regular, but limited interaction is found to promote correct learning by enlarging the parameter region where it occurs.

  9. Social Networks of Educated Nematodes.

    Science.gov (United States)

    Willett, Denis S; Alborn, Hans T; Duncan, Larry W; Stelinski, Lukasz L

    2015-09-25

    Entomopathogenic nematodes are obligate lethal parasitoids of insect larvae that navigate a chemically complex belowground environment while interacting with their insect hosts, plants, and each other. In this environment, prior exposure to volatile compounds appears to prime nematodes in a compound specific manner, increasing preference for volatiles they previously were exposed to and decreasing attraction to other volatiles. In addition, persistence of volatile exposure influences this response. Longer exposure not only increases preference, but also results in longer retention of that preference. These entomopathogenic nematodes display interspecific social behavioral plasticity; experienced nematodes influence the behavior of different species. This interspecific social behavioral plasticity suggests a mechanism for rapid adaptation of belowground communities to dynamic environments.

  10. Pinning Synchronization of Switched Complex Dynamical Networks

    Directory of Open Access Journals (Sweden)

    Liming Du

    2015-01-01

    Full Text Available Network topology and node dynamics play a key role in forming synchronization of complex networks. Unfortunately there is no effective synchronization criterion for pinning synchronization of complex dynamical networks with switching topology. In this paper, pinning synchronization of complex dynamical networks with switching topology is studied. Two basic problems are considered: one is pinning synchronization of switched complex networks under arbitrary switching; the other is pinning synchronization of switched complex networks by design of switching when synchronization cannot achieved by using any individual connection topology alone. For the two problems, common Lyapunov function method and single Lyapunov function method are used respectively, some global synchronization criteria are proposed and the designed switching law is given. Finally, simulation results verify the validity of the results.

  11. 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)...

  12. Exploring the morphospace of communication efficiency in complex networks.

    Science.gov (United States)

    Goñi, Joaquín; Avena-Koenigsberger, Andrea; Velez de Mendizabal, Nieves; van den Heuvel, Martijn P; Betzel, Richard F; Sporns, Olaf

    2013-01-01

    Graph theoretical analysis has played a key role in characterizing global features of the topology of complex networks, describing diverse systems such as protein interactions, food webs, social relations and brain connectivity. How system elements communicate with each other depends not only on the structure of the network, but also on the nature of the system's dynamics which are constrained by the amount of knowledge and resources available for communication processes. Complementing widely used measures that capture efficiency under the assumption that communication preferentially follows shortest paths across the network ("routing"), we define analytic measures directed at characterizing network communication when signals flow in a random walk process ("diffusion"). The two dimensions of routing and diffusion efficiency define a morphospace for complex networks, with different network topologies characterized by different combinations of efficiency measures and thus occupying different regions of this space. We explore the relation of network topologies and efficiency measures by examining canonical network models, by evolving networks using a multi-objective optimization strategy, and by investigating real-world network data sets. Within the efficiency morphospace, specific aspects of network topology that differentially favor efficient communication for routing and diffusion processes are identified. Charting regions of the morphospace that are occupied by canonical, evolved or real networks allows inferences about the limits of communication efficiency imposed by connectivity and dynamics, as well as the underlying selection pressures that have shaped network topology.

  13. Exploring the morphospace of communication efficiency in complex networks.

    Directory of Open Access Journals (Sweden)

    Joaquín Goñi

    Full Text Available Graph theoretical analysis has played a key role in characterizing global features of the topology of complex networks, describing diverse systems such as protein interactions, food webs, social relations and brain connectivity. How system elements communicate with each other depends not only on the structure of the network, but also on the nature of the system's dynamics which are constrained by the amount of knowledge and resources available for communication processes. Complementing widely used measures that capture efficiency under the assumption that communication preferentially follows shortest paths across the network ("routing", we define analytic measures directed at characterizing network communication when signals flow in a random walk process ("diffusion". The two dimensions of routing and diffusion efficiency define a morphospace for complex networks, with different network topologies characterized by different combinations of efficiency measures and thus occupying different regions of this space. We explore the relation of network topologies and efficiency measures by examining canonical network models, by evolving networks using a multi-objective optimization strategy, and by investigating real-world network data sets. Within the efficiency morphospace, specific aspects of network topology that differentially favor efficient communication for routing and diffusion processes are identified. Charting regions of the morphospace that are occupied by canonical, evolved or real networks allows inferences about the limits of communication efficiency imposed by connectivity and dynamics, as well as the underlying selection pressures that have shaped network topology.

  14. The Fractal Dimensions of Complex Networks

    Institute of Scientific and Technical Information of China (English)

    GUO Long; CAI Xu

    2009-01-01

    It is shown that many real complex networks share distinctive features,such as the small-world effect and the heterogeneous property of connectivity of vertices,which are different from random networks and regular lattices.Although these features capture the important characteristics of complex networks,their applicability depends on the style of networks.To unravel the universal characteristics many complex networks have in common,we study the fractal dimensions of complex networks using the method introduced by Shanker.We lind that the average 'density' (p(r)) of complex networks follows a better power-law function as a function of distance r with the exponent df,which is defined as the fractal dimension,in some real complex networks.Furthermore,we study the relation between df and the shortcuts Nadd in small-world networks and the size N in regular lattices.Our present work provides a new perspective to understand the dependence of the fractal dimension df on the complex network structure.

  15. Predicting Anchor Links between Heterogeneous Social Networks

    CERN Document Server

    Sajadmanesh, Sina; Khodadadi, Ali

    2016-01-01

    People usually get involved in multiple social networks to enjoy new services or to fulfill their needs. Many new social networks try to attract users of other existing networks to increase the number of their users. Once a user (called source user) of a social network (called source network) joins a new social network (called target network), a new inter-network link (called anchor link) is formed between the source and target networks. In this paper, we concentrated on predicting the formation of such anchor links between heterogeneous social networks. Unlike conventional link prediction problems in which the formation of a link between two existing users within a single network is predicted, in anchor link prediction, the target user is missing and will be added to the target network once the anchor link is created. To solve this problem, we use meta-paths as a powerful tool for utilizing heterogeneous information in both the source and target networks. To this end, we propose an effective general meta-pat...

  16. Introduction to focus issue: mesoscales in complex networks.

    Science.gov (United States)

    Almendral, Juan A; Criado, Regino; Leyva, Inmaculada; Buldú, Javier M; Sendiña-Nadal, Irene

    2011-03-01

    Although the functioning of real complex networks is greatly determined by modularity, the majority of articles have focused, until recently, on either their local scale structure or their macroscopical properties. However, neither of these descriptions can adequately describe the important features that complex networks exhibit due to their organization in modules. This Focus Issue precisely presents the state of the art on the study of complex networks at that intermediate level. The reader will find out why this mesoscale level has become an important topic of research through the latest advances carried out to improve our understanding of the dynamical behavior of modular networks. The contributions presented here have been chosen to cover, from different viewpoints, the many open questions in the field as different aspects of community definition and detection algorithms, moduli overlapping, dynamics on modular networks, interplay between scales, and applications to biological, social, and technological fields.

  17. 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.

  18. Mobile Social Network in a Cultural Context

    DEFF Research Database (Denmark)

    Liu, Jun

    2010-01-01

    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......, 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....

  19. Properties of Bottleneck on Complex Networks

    Institute of Scientific and Technical Information of China (English)

    WANG Chao-Yang; WU Jian-Jun; GAO Zi-You

    2011-01-01

    The traffic bottleneck plays a key role in most of the natural and artificial network.Here we present a simply model for bottleneck dynamical characteristics consideration the reliability on the complex network by taking into account the network topology characteristics and system size.We find that there is a critical rate of flow generation below which the network traffic is free but above which traffic congestion occurs.Also, it is found that random networks have larger critical flow generating rate than scale free ones.Analytical results may be practically useful for designing networks, especially for the urban traffic network.

  20. Visualization Through Knowledge Representation Model for Social Networks

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar; Athar Javed, Muhammad; Ahmed, Zaki

    2011-01-01

    the process of knowing, learning and creating knowledge is the relevant aspect (Nonaka and Takeuchi 1995). In this paper knowledge representation is presented in 3D style for the understanding and visualization of dynamics of complex social networks by developing a TANetworkTool (Task Analysis Network Tool....... Although, many analytical methods provide relationship dependencies, role of different nodes and their importance in the network. In this paper we are presenting a visualization of networks by rotating the network through various dimensions to provide a more realistic view to understand the dynamics...

  1. 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.

  2. SOCIAL NETWORK ANALYSIS IN AN ONLINE BLOGOSPHERE

    Directory of Open Access Journals (Sweden)

    DR. M. MOHAMED SATHIK

    2011-01-01

    Full Text Available Social network is a social structure that exists among the similar interest of individuals, organizations or even on relations like friendship. Social network analysis is the measure of relationship between people, organizations and processing entities. In today’s scenario, Internet is acting as an interface for the people who spread across the globe to exchange their ideas. Social network analysis is a Web 2.0 application, which facilitates the users tointeract, response and express their views. Social network analysis has greatest attention as a research area in computer science in the recent past. Blogs or weblogs are like catalogs that are maintained by individuals related to a particular topic of interest. In this problem, we analyze the blog responses as social networks that are posted by AIDS patients over a period of time.

  3. Discovering universal statistical laws of complex networks

    CERN Document Server

    Cardanobile, Stefano; Deger, Moritz; Rotter, Stefan

    2011-01-01

    Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their generalisation power, which we identify with large structural variability and absence of constraints imposed by the construction scheme. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This allows, for instance, to infer global features from local ones usi...

  4. How to Measure Significance of Community Structure in Complex Networks

    CERN Document Server

    Hu, Yanqing; Fan, Ying; Di, Zengru

    2010-01-01

    Community structure analysis is a powerful tool for complex networks, which can simplify their functional analysis considerably. Recently, many approaches were proposed to community structure detection, but few works were focused on the significance of community structure. Since real networks obtained from complex systems always contain error links, and most of the community detection algorithms have random factors, evaluate the significance of community structure is important and urgent. In this paper, we use the eigenvectors' stability to characterize the significance of community structures. By employing the eigenvalues of Laplacian matrix of a given network, we can evaluate the significance of its community structure and obtain the optimal number of communities, which are always hard for community detection algorithms. We apply our method to many real networks. We find that significant community structures exist in many social networks and C.elegans neural network, and that less significant community stru...

  5. 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%.

  6. 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%.

  7. Hypergraph topological quantities for tagged social networks

    Science.gov (United States)

    Zlatić, Vinko; Ghoshal, Gourab; Caldarelli, Guido

    2009-09-01

    Recent years have witnessed the emergence of a new class of social networks, which require us to move beyond previously employed representations of complex graph structures. A notable example is that of the folksonomy, an online process where users collaboratively employ tags to resources to impart structure to an otherwise undifferentiated database. In a recent paper, we proposed a mathematical model that represents these structures as tripartite hypergraphs and defined basic topological quantities of interest. In this paper, we extend our model by defining additional quantities such as edge distributions, vertex similarity and correlations as well as clustering. We then empirically measure these quantities on two real life folksonomies, the popular online photo sharing site Flickr and the bookmarking site CiteULike. We find that these systems share similar qualitative features with the majority of complex networks that have been previously studied. We propose that the quantities and methodology described here can be used as a standard tool in measuring the structure of tagged networks.

  8. 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.

  9. 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…

  10. 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…

  11. Web Mining and Social Networking

    DEFF Research Database (Denmark)

    Xu, Guandong; Zhang, Yanchun; Li, Lin

    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...

  12. ONLINE SOCIAL NETWORK INTERNETWORKING ANALYSIS

    Directory of Open Access Journals (Sweden)

    Bassant E.Youssef

    2014-10-01

    Full Text Available Online social networks (OSNs contain data about users, their relations, interests and daily activities andthe great value of this data results in ever growing popularity of OSNs. There are two types of OSNs data,semantic and topological. Both can be used to support decision making processes in many applicationssuch as in information diffusion, viral marketing and epidemiology. Online Social network analysis (OSNAresearch is used to maximize the benefits gained from OSNs’ data. This paper provides a comprehensive study of OSNs and OSNA to provide analysts with the knowledge needed to analyse OSNs. OSNs’internetworking was found to increase the wealth of the analysed data by depending on more than one OSNas the source of the analysed data. Paper proposes a generic model of OSNs’ internetworking system that an analyst can rely on. Twodifferent data sources in OSNs were identified in our efforts to provide a thorough study of OSNs, whichare the OSN User data and the OSN platform data. Additionally, we propose a classification of the OSNUser data according to its analysis models for different data types to shed some light into the current usedOSNA methodologies. We also highlight the different metrics and parameters that analysts can use toevaluate semantic or topologic OSN user data. Further, we present a classification of the other data typesand OSN platform data that can be used to compare the capabilities of different OSNs whether separate orin a OSNs’ internetworking system. To increase analysts’ awareness about the available tools they can use,we overview some of the currently publically available OSNs’ datasets and simulation tools and identifywhether they are capable of being used in semantic, topological OSNA, or both. The overview identifiesthat only few datasets includes both data types (semantic and topological and there are few analysis toolsthat can perform analysis on both data types. Finally paper present a scenario that

  13. Approaching human language with complex networks

    Science.gov (United States)

    Cong, Jin; Liu, Haitao

    2014-12-01

    The interest in modeling and analyzing human language with complex networks is on the rise in recent years and a considerable body of research in this area has already been accumulated. We survey three major lines of linguistic research from the complex network approach: 1) characterization of human language as a multi-level system with complex network analysis; 2) linguistic typological research with the application of linguistic networks and their quantitative measures; and 3) relationships between the system-level complexity of human language (determined by the topology of linguistic networks) and microscopic linguistic (e.g., syntactic) features (as the traditional concern of linguistics). We show that the models and quantitative tools of complex networks, when exploited properly, can constitute an operational methodology for linguistic inquiry, which contributes to the understanding of human language and the development of linguistics. We conclude our review with suggestions for future linguistic research from the complex network approach: 1) relationships between the system-level complexity of human language and microscopic linguistic features; 2) expansion of research scope from the global properties to other levels of granularity of linguistic networks; and 3) combination of linguistic network analysis with other quantitative studies of language (such as quantitative linguistics).

  14. 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.

  15. Local Natural Connectivity in Complex Networks

    Institute of Scientific and Technical Information of China (English)

    SHANG Yi-Lun

    2011-01-01

    @@ In network theory, a complex network represents a system whose evolving structure and dynamic behavior contribute to its robustness.The natural connectivity is recently proposed as a spectral measure to characterize the robustness of complex networks.We decompose the natural connectivity of a network as local natural connectivity of its connected components and quantify their contributions to the network robustness.In addition, we compare the natural connectivity of a network with that of an induced subgraph of it based on interlacing theorems.As an application, we derive an inequality for eigenvalues of ErdSs-Renyi random graphs.%In network theory, a complex network represents a system whose evolving structure and dynamic behavior contribute to its robustness. The natural connectivity is recently proposed as a spectral measure to characterize the robustness of complex networks. We decompose the natural connectivity of a network as local naturai connectivity of its connected components and quantify their contributions to the network robustness. In addition, we compare the naturai connectivity of a network with that of an induced subgraph of it based on interlacing theorems. As an application, we derive an inequality for eigenvalues of Erdos-Renyi random graphs.

  16. Pinning-controllability of complex networks

    OpenAIRE

    Sorrentino, Francesco; Di Bernardo, Mario; Garofalo, Franco; Chen, Guanrong

    2007-01-01

    We study the problem of controlling a general complex network towards an assigned synchronous evolution, by means of a pinning control strategy. We define the pinning-controllability of the network in terms of the spectral properties of an extended network topology. The roles of the control and coupling gains as well as of the number of pinned nodes are also discussed.

  17. 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...

  18. Modelling the structure of complex networks

    DEFF Research Database (Denmark)

    Herlau, Tue

    networks has been independently studied as mathematical objects in their own right. As such, there has been both an increased demand for statistical methods for complex networks as well as a quickly growing mathematical literature on the subject. In this dissertation we explore aspects of modelling complex....... The next chapters will treat some of the various symmetries, representer theorems and probabilistic structures often deployed in the modelling complex networks, the construction of sampling methods and various network models. The introductory chapters will serve to provide context for the included written...

  19. 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.

  20. 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.

  1. Synchronization in complex networks with adaptive coupling

    Science.gov (United States)

    Zhang, Rong; Hu, Manfeng; Xu, Zhenyuan

    2007-08-01

    Generally it is very difficult to realized synchronization for some complex networks. In order to synchronize, the coupling coefficient of networks has to be very large, especially when the number of coupled nodes is larger. In this Letter, we consider the problem of synchronization in complex networks with adaptive coupling. A new concept about asymptotic stability is presented, then we proved by using the well-known LaSalle invariance principle, that the state of such a complex network can synchronize an arbitrary assigned state of an isolated node of the network as long as the feedback gain is positive. Unified system is simulated as the nodes of adaptive coupling complex networks with different topologies.

  2. Synchronization in complex networks with adaptive coupling

    Energy Technology Data Exchange (ETDEWEB)

    Zhang Rong [School of Science, Southern Yangtze University, Wuxi 214122 (China); School of Information Engineering, Southern Yangtze University, Wuxi 214122 (China)], E-mail: ronia62@yahoo.com; Hu Manfeng [School of Science, Southern Yangtze University, Wuxi 214122 (China); School of Information Engineering, Southern Yangtze University, Wuxi 214122 (China); Xu Zhenyuan [School of Science, Southern Yangtze University, Wuxi 214122 (China)

    2007-08-20

    Generally it is very difficult to realized synchronization for some complex networks. In order to synchronize, the coupling coefficient of networks has to be very large, especially when the number of coupled nodes is larger. In this Letter, we consider the problem of synchronization in complex networks with adaptive coupling. A new concept about asymptotic stability is presented, then we proved by using the well-known LaSalle invariance principle, that the state of such a complex network can synchronize an arbitrary assigned state of an isolated node of the network as long as the feedback gain is positive. Unified system is simulated as the nodes of adaptive coupling complex networks with different topologies.

  3. Complex Networks of Words in Fables

    CERN Document Server

    Holovatch, Yurij

    2016-01-01

    In this chapter we give an overview of the application of complex network theory to quantify some properties of language. Our study is based on two fables in Ukrainian, Mykyta the Fox and Abu-Kasym's slippers. It consists of two parts: the analysis of frequency-rank distributions of words and the application of complex-network theory. The first part shows that the text sizes are sufficiently large to observe statistical properties. This supports their selection for the analysis of typical properties of the language networks in the second part of the chapter. In describing language as a complex network, while words are usually associated with nodes, there is more variability in the choice of links and different representations result in different networks. Here, we examine a number of such representations of the language network and perform a comparative analysis of their characteristics. Our results suggest that, irrespective of link representation, the Ukrainian language network used in the selected fables i...

  4. Pinning impulsive control algorithms for complex network.

    Science.gov (United States)

    Sun, Wen; Lü, Jinhu; Chen, Shihua; Yu, Xinghuo

    2014-03-01

    In this paper, we further investigate the synchronization of complex dynamical network via pinning control in which a selection of nodes are controlled at discrete times. Different from most existing work, the pinning control algorithms utilize only the impulsive signals at discrete time instants, which may greatly improve the communication channel efficiency and reduce control cost. Two classes of algorithms are designed, one for strongly connected complex network and another for non-strongly connected complex network. It is suggested that in the strongly connected network with suitable coupling strength, a single controller at any one of the network's nodes can always pin the network to its homogeneous solution. In the non-strongly connected case, the location and minimum number of nodes needed to pin the network are determined by the Frobenius normal form of the coupling matrix. In addition, the coupling matrix is not necessarily symmetric or irreducible. Illustrative examples are then given to validate the proposed pinning impulsive control algorithms.

  5. On the Behaviour of Deviant Communities in Online Social Networks

    CERN Document Server

    Coletto, Mauro; Lucchese, Claudio; Silvestri, Fabrizio

    2016-01-01

    On-line social networks are complex ensembles of inter-linked communities that interact on different topics. Some communities are characterized by what are usually referred to as deviant behaviors, conducts that are commonly considered inappropriate with respect to the society's norms or moral standards. Eating disorders, drug use, and adult content consumption are just a few examples. We refer to such communities as deviant networks. It is commonly believed that such deviant networks are niche, isolated social groups, whose activity is well separated from the mainstream social-media life. According to this assumption, research studies have mostly considered them in isolation. In this work we focused on adult content consumption networks, which are present in many on-line social media and in the Web in general. We found that few small and densely connected communities are responsible for most of the content production. Differently from previous work, we studied how such communities interact with the whole soc...

  6. Controlling Congestion on Complex Networks

    CERN Document Server

    Buzna, Lubos

    2016-01-01

    From the Internet to road networks and the power grid, modern life depends on controlling flows on critical infrastructure networks that often operate in a congested state. Yet, we have a limited understanding of the relative performance of the control mechanisms available to manage congestion and of the interplay between network topology, path layout and congestion control algorithms. Here, we consider two flow algorithms (max-flow and uniform-flow), and two more realistic congestion control schemes (max-min fairness and proportional fairness). We analyse how the algorithms and network topology affect throughput, fairness and the location of bottleneck edges. Our results show that on large random networks a network operator can implement the trade-off (proportional fairness) instead of the fair allocation (max-min fairness) with little sacrifice in throughput. We illustrate how the previously studied uniform-flow approach leaves networks severely underutilised in comparison with congestion control algorithms...

  7. Enhancing Classroom Effectiveness through Social Networking Tools

    Science.gov (United States)

    Kurthakoti, Raghu; Boostrom, Robert E., Jr.; Summey, John H.; Campbell, David A.

    2013-01-01

    To determine the usefulness of social networking Web sites such as Ning.com as a communication tool in marketing courses, a study was designed with special concern for social network use in comparison to Blackboard. Students from multiple marketing courses were surveyed. Assessments of Ning.com and Blackboard were performed both to understand how…

  8. Mapping social networks in software process improvement

    DEFF Research Database (Denmark)

    Tjørnehøj, Gitte; Nielsen, Peter Axel

    2005-01-01

    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...

  9. Social Networks: Gated Communities or Free Cantons?

    CERN Document Server

    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?

  10. 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…

  11. Intercultural Communication in Online Social Networking Discourse

    Science.gov (United States)

    Chen, Hsin-I

    2017-01-01

    This article presents a case study that examines how an online social networking community is constituted through intercultural discourse on the part of one learner sojourning in the US. Using Byram's model of intercultural communicative competence, this study examines the learner's naturalistic communication in a social networking site (SNS). The…

  12. Social networking sites and adolescent health.

    Science.gov (United States)

    Moreno, Megan A; Kolb, Jennifer

    2012-06-01

    Social networking sites are popular among and consistently used by adolescents. These sites present benefits as well as risks to adolescent health. Recently, pediatric providers have also considered the benefits and risks of using social networking sites in their own practices.

  13. 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…

  14. Mapping social networks in software process improvement

    DEFF Research Database (Denmark)

    Tjørnehøj, Gitte; Nielsen, Peter Axel

    2005-01-01

    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...

  15. 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…

  16. 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…

  17. 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

  18. Complex networks analysis in socioeconomic models

    CERN Document Server

    Varela, Luis M; Ausloos, Marcel; Carrete, Jesus

    2014-01-01

    This chapter aims at reviewing complex networks models and methods that were either developed for or applied to socioeconomic issues, and pertinent to the theme of New Economic Geography. After an introduction to the foundations of the field of complex networks, the present summary adds insights on the statistical mechanical approach, and on the most relevant computational aspects for the treatment of these systems. As the most frequently used model for interacting agent-based systems, a brief description of the statistical mechanics of the classical Ising model on regular lattices, together with recent extensions of the same model on small-world Watts-Strogatz and scale-free Albert-Barabasi complex networks is included. Other sections of the chapter are devoted to applications of complex networks to economics, finance, spreading of innovations, and regional trade and developments. The chapter also reviews results involving applications of complex networks to other relevant socioeconomic issues, including res...

  19. Securing Information with Complex Optical Encryption Networks

    Science.gov (United States)

    2015-08-11

    Encryption Networks 5a. CONTRACT NUMBER FA2386-13-1-4106 5b. GRANT NUMBER Grant AOARD-134106 5c. PROGRAM ELEMENT NUMBER 61102F 6. AUTHOR(S...configure complex optical encryption networks for securing information. The goal is to study/develop the architectures for a number of complex optical... encryption networks, and to provide effective and reliable solutions for information security. 15. SUBJECT TERMS Optical Encryption

  20. Social relations: network, support and relational strain

    DEFF Research Database (Denmark)

    Due, P; Holstein, B; Lund, Rikke

    1999-01-01

    ,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......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......, social anchorage and relational strain. We use this conceptual framework to describe social relations in the Danish population, with questionnaire data from the Danish Longitudinal Health Behaviour Study including a random sample of each of the age groups 25-, 50-, 60-and 70-year olds, N = 2...

  1. Complex Network Analysis of Brazilian Power Grid

    CERN Document Server

    Martins, Gabriela C; Ribeiro, Fabiano L; Forgerini, Fabricio L

    2016-01-01

    Power Grids and other delivery networks has been attracted some attention by the network literature last decades. Despite the Power Grids dynamics has been controlled by computer systems and human operators, the static features of this type of network can be studied and analyzed. The topology of the Brazilian Power Grid (BPG) was studied in this work. We obtained the spatial structure of the BPG from the ONS (electric systems national operator), consisting of high-voltage transmission lines, generating stations and substations. The local low-voltage substations and local power delivery as well the dynamic features of the network were neglected. We analyze the complex network of the BPG and identify the main topological information, such as the mean degree, the degree distribution, the network size and the clustering coefficient to caracterize the complex network. We also detected the critical locations on the network and, therefore, the more susceptible points to lead to a cascading failure and even to a blac...

  2. Visualizing global properties of large complex networks.

    Directory of Open Access Journals (Sweden)

    Weijiang Li

    Full Text Available For complex biological networks, graphical representations are highly desired for understanding some design principles, but few drawing methods are available that capture topological features of a large and highly heterogeneous network, such as a protein interaction network. Here we propose the circular perspective drawing (CPD method to visualize global structures of large complex networks. The presented CPD combines the quasi-continuous search (QCS analogous to the steepest descent method with a random node swapping strategy for an enhanced calculation speed. The CPD depicts a network in an aesthetic manner by showing connection patterns between different parts of the network instead of detailed links between nodes. Global structural features of networks exhibited by CPD provide clues toward a comprehensive understanding of the network organizations.Software is freely available at http://www.cadlive.jp.

  3. 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.

  4. Dynamics of deceptive interactions in social networks

    CERN Document Server

    Barrio, Rafael A; Dunbar, Robin; Iñiguez, Gerardo; Kaski, Kimmo

    2015-01-01

    In this paper we examine the role of lies in human social relations by implementing some salient characteristics of deceptive interactions into an opinion formation model, so as to describe the dynamical behaviour of a social network more realistically. In this model we take into account such basic properties of social networks as the dynamics of the intensity of interactions, the influence of public opinion, and the fact that in every human interaction it might be convenient to deceive or withhold information depending on the instantaneous situation of each individual in the network. We find that lies shape the topology of social networks, especially the formation of tightly linked, small communities with loose connections between them. We also find that agents with a larger proportion of deceptive interactions are the ones that connect communities of different opinion, and in this sense they have substantial centrality in the network. We then discuss the consequences of these results for the social behaviou...

  5. Firm Performance-A Social Networks Perspective

    Directory of Open Access Journals (Sweden)

    Jane Tung

    2012-01-01

    Full Text Available Problem statement: The study aims to offer a discussion on social networks and their effect on firm performance and also to illustrate the ways by which the firms utilize social capital through networks. Approach: The literature review and arguments were conducted to provide a systematic discussion of social networks and their effects. Results: The study had provided with a detailed understanding of the strategies that had been found to be highly significant in successful organizational performance. The results of this discussion suggested that social networks affect firm performance in a positive manner and can contribute to sustainable competitive advantage. Conclusion: It confirms that building up of social networks for big and small firms provides valuable links and solves numerous issues which auger well for the companies and should be treated with great importance.

  6. The independent spreaders involved SIR Rumor model in complex networks

    Science.gov (United States)

    Qian, Zhen; Tang, Shaoting; Zhang, Xiao; Zheng, Zhiming

    2015-07-01

    Recent studies of rumor or information diffusion process in complex networks show that in contrast to traditional comprehension, individuals who participate in rumor spreading within one network do not always get the rumor from their neighbors. They can obtain the rumor from different sources like online social networks and then publish it on their personal sites. In our paper, we discuss this phenomenon in complex networks by adopting the concept of independent spreaders. Rather than getting the rumor from neighbors, independent spreaders learn it from other channels. We further develop the classic "ignorant-spreaders-stiflers" or SIR model of rumor diffusion process in complex networks. A steady-state analysis is conducted to investigate the final spectrum of the rumor spreading under various spreading rate, stifling rate, density of independent spreaders and average degree of the network. Results show that independent spreaders effectively enhance the rumor diffusion process, by delivering the rumor to regions far away from the current rumor infected regions. And though the rumor spreading process in SF networks is faster than that in ER networks, the final size of rumor spreading in ER networks is larger than that in SF networks.

  7. Social Network Influence on Online Behavioral Choices: Exploring Group Formation on Social Network Sites

    OpenAIRE

    Kwon, KH; Stefanone, MA; Barnett, GA

    2014-01-01

    Social media communication is characterized by reduced anonymity and off-to-online social interactions. These characteristics require scholars to revisit social influence mechanisms online. The current study builds on social influence literature to explore social network and gender effects on online behavior. Findings from a quasi-experiment suggest that both network-related variables and gender are significantly associated with online behavior. Perceived social environment, measured by perso...

  8. Understanding the Complexity of Terrorist Networks

    CERN Document Server

    Fellman, Philip V

    2009-01-01

    Complexity science affords a number of novel tools for examining terrorism, particularly network analysis and NK-Boolean fitness landscapes. The following paper explores various aspects of terrorist networks which can be illuminated through applications of non-linear dynamical systems modeling to terrorist network structures. Of particular interest are some of the emergent properties of terrorist networks as typified by the 9-11 hijackers network, properties of centrality, hierarchy and distance, as well as ways in which attempts to disrupt the transmission of information through terrorist networks may be expected to produce greater or lesser levels of fitness in those organizations.

  9. Social Complexity: can it be analyzed and modelled?

    CERN Document Server

    Kaski, Kimmo

    2010-01-01

    Over the past decade network theory has turned out to be a powerful methodology to investigate complex systems of various sorts. Through data analysis, modeling, and simulation quite an unparalleled insight into their structure, function, and response can be obtained. In human societies individuals are linked through social interactions, which today are increasingly mediated electronically by modern Information Communication Technology thus leaving "footprints" of human behaviour as digital records. For these datasets the network theory approach is a natural one as we have demonstrated by analysing the dataset of multi-million user mobile phone communication-logs. This social network turned out to be modular in structure showing communities where individuals are connected with stronger ties and between communities with weaker ties. Also the network topology and the weighted links for pairs of individuals turned out to be related.These empirical findings inspired us to take the next step in network theory, by ...

  10. 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.

  11. Information filtering on coupled social networks.

    Directory of Open Access Journals (Sweden)

    Da-Cheng Nie

    Full Text Available 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.

  12. Preserving Communities in Anonymized Social Networks

    Directory of Open Access Journals (Sweden)

    Alina Campan

    2015-04-01

    Full Text Available Social media and social networks are embedded in our society to a point that could not have been imagined only ten years ago. Facebook, LinkedIn, and Twitter are already well known social networks that have a large audience in all age groups. The amount of data that those social sites gather from their users is continually increasing and this data is very valuable for marketing, research, and various other purposes. At the same time, this data usually contain a significant amount of sensitive information which should be protected against unauthorized disclosure. To protect the privacy of individuals, this data must be anonymized such that the risk of re-identification of specific individuals is very low. In this paper we study if anonymized social networks preserve existing communities from the original social networks. To perform this study, we introduce two approaches to measure the community preservation between the initial network and its anonymized version. In the first approach we simply count how many nodes from the original communities remained in the same community after the processes of anonymization and de-anonymization. In the second approach we consider the community preservation for each node individually. Specifically, for each node, we compare the original and final communities to which the node belongs. To anonymize social networks we use two models, namely, k-anonymity for social networks and k-degree anonymity. To determine communities in social networks we use an existing community detection algorithm based on modularity quality function. Our experiments on publically available datasets show that anonymized social networks satisfactorily preserve the community structure of their original networks.

  13. 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

  14. 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.

  15. 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 d

  16. 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.

  17. Social Network Analyses and Nutritional Behavior: An Integrated Modeling Approach

    Directory of Open Access Journals (Sweden)

    Alistair McNair Senior

    2016-01-01

    Full Text Available Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent advances in nutrition research, combining state-space models of nutritional geometry with agent-based models of systems biology, show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a tangible and practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit agent-based models that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition. Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interaction in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments.

  18. Social Network Analysis and Nutritional Behavior: An Integrated Modeling Approach.

    Science.gov (United States)

    Senior, Alistair M; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J

    2016-01-01

    Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments.

  19. 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.

  20. Transparency effect in the emergence of monopolies in social networks

    CERN Document Server

    Shirazi, A H; Roohi, A A; Jafari, G R

    2013-01-01

    Power law degree distribution was shown in many complex networks. However, in most real systems, deviation from power-law behavior is observed in social and economical networks and emergence of giant hubs is obvious in real network structures far from the tail of power law. We propose a model based on the information transparency (transparency means how much the information is obvious to others). This model can explain power structure in societies with non-transparency in information delivery. The emergence of ultra powerful nodes is explained as a direct result of censorship. Based on these assumptions, we define four distinct transparency regions: perfect non-transparent, low transparent, perfect transparent and exaggerated regions. We observe the emergence of some ultra powerful (very high degree) nodes in low transparent networks, in accordance with the economical and social systems. We show that the low transparent networks are more vulnerable to attacks and the controllability of low transparent network...

  1. Socially-Aware Networking: A Survey

    OpenAIRE

    Xia, Feng; Liu, Li; Li, Jie; Ma, Jianhua; Vasilakos, Athanasios V.

    2013-01-01

    The widespread proliferation of handheld devices enables mobile carriers to be connected at anytime and anywhere. Meanwhile, the mobility patterns of mobile devices strongly depend on the users' movements, which are closely related to their social relationships and behaviors. Consequently, today's mobile networks are becoming increasingly human centric. This leads to the emergence of a new field which we call socially-aware networking (SAN). One of the major features of SAN is that social awa...

  2. DEPENDENCE ON SOCIAL NETWORKING SITES IN ADOLESCENTS

    Directory of Open Access Journals (Sweden)

    Ranjith

    2016-03-01

    Full Text Available 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, interact with real life friends and meet other people based on shared interests. Negative correlates of Social Networking Sites usage include the decrease in real life social community participation and academic achievement as well as relationship problems, each of which may be indicative of potential addiction. AIMS AND OBJECTIVES To study and assess the dependence on social networking sites among medical college students of adolescent age group. MATERIALS AND METHODOLOGY 200 subjects, both boys and girls were included in the cross-sectional study who were given a 20-item Young’s internet addiction test modified for social networking sites. The responses were analysed using Chi square test and Fisher’s exact test. RESULTS Of 198 students, 24.74% of them had occasional or ‘frequency’ problems, while 2.02% of them were experiencing severe problems due to excessive time spent using social networking sites and boys spent excessive time on internet compared to girls. CONCLUSION With the growth of technology and increasing popularity of social media, social networking sites have become a part and parcel of adolescent life. Though it is helping students in emotional development and connecting with friends and family, adolescents are devoting significant time to social networking on websites and are prone to become dependent to such form of online social interaction which can affect their academics and decrease real life social community participation.

  3. SOCIAL NETWORKS AS DISPOSITIVES OF NEOLIBERAL GOVERNMENTALITY

    OpenAIRE

    Julio Cesar Lemes de Castro

    2016-01-01

    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 neolibera...

  4. Structural Holes in Directed Fuzzy Social Networks

    OpenAIRE

    Renjie Hu; Guangyu Zhang

    2014-01-01

    The structural holes have been a key issue in fuzzy social network analysis. For undirected fuzzy social networks where edges are just present or absent undirected fuzzy relation and have no more information attached, many structural holes measures have been presented, such as key fuzzy structural holes, general fuzzy structural holes, strong fuzzy structural holes, and weak fuzzy structural holes. There has been a growing need to design structural holes measures for directed fuzzy social net...

  5. An Introduction to Social Network Data Analytics

    Science.gov (United States)

    Aggarwal, Charu C.

    The advent of online social networks has been one of the most exciting events in this decade. Many popular online social networks such as Twitter, LinkedIn, and Facebook have become increasingly popular. In addition, a number of multimedia networks such as Flickr have also seen an increasing level of popularity in recent years. Many such social networks are extremely rich in content, and they typically contain a tremendous amount of content and linkage data which can be leveraged for analysis. The linkage data is essentially the graph structure of the social network and the communications between entities; whereas the content data contains the text, images and other multimedia data in the network. The richness of this network provides unprecedented opportunities for data analytics in the context of social networks. This book provides a data-centric view of online social networks; a topic which has been missing from much of the literature. This chapter provides an overview of the key topics in this field, and their coverage in this book.

  6. Constrained target controllability of complex networks

    Science.gov (United States)

    Guo, Wei-Feng; Zhang, Shao-Wu; Wei, Ze-Gang; Zeng, Tao; Liu, Fei; Zhang, Jingsong; Wu, Fang-Xiang; Chen, Luonan

    2017-06-01

    It is of great theoretical interest and practical significance to study how to control a system by applying perturbations to only a few driver nodes. Recently, a hot topic of modern network researches is how to determine driver nodes that allow the control of an entire network. However, in practice, to control a complex network, especially a biological network, one may know not only the set of nodes which need to be controlled (i.e. target nodes), but also the set of nodes to which only control signals can be applied (i.e. constrained control nodes). Compared to the general concept of controllability, we introduce the concept of constrained target controllability (CTC) of complex networks, which concerns the ability to drive any state of target nodes to their desirable state by applying control signals to the driver nodes from the set of constrained control nodes. To efficiently investigate the CTC of complex networks, we further design a novel graph-theoretic algorithm called CTCA to estimate the ability of a given network to control targets by choosing driver nodes from the set of constrained control nodes. We extensively evaluate the CTC of numerous real complex networks. The results indicate that biological networks with a higher average degree are easier to control than biological networks with a lower average degree, while electronic networks with a lower average degree are easier to control than web networks with a higher average degree. We also show that our CTCA can more efficiently produce driver nodes for target-controlling the networks than existing state-of-the-art methods. Moreover, we use our CTCA to analyze two expert-curated bio-molecular networks and compare to other state-of-the-art methods. The results illustrate that our CTCA can efficiently identify proven drug targets and new potentials, according to the constrained controllability of those biological networks.

  7. Evolution Properties of Modules in Complex Networks

    Institute of Scientific and Technical Information of China (English)

    LI Ke-Ping; GAO Zi-You

    2008-01-01

    In complex networks, network modules play a center role, which carry out a key function. In this paper, we introduce the spatial correlation function to describe the relationships among the network modules. Our focus is to investigate how the network modules evolve, and what the evolution properties of the modules are. In order to test the proposed method, as the examples, we use our method to analyze and discuss the ER random network and scale-free network. Rigorous analysis of the existing data shows that the introduced correlation function is suitable for describing the evolution properties of network modules. Remarkably, the numerical simulations indicate that the ER random network and scale-free network have different evolution properties.

  8. Revealing the Hidden Language of Complex Networks

    Science.gov (United States)

    Yaveroğlu, Ömer Nebil; Malod-Dognin, Noël; Davis, Darren; Levnajic, Zoran; Janjic, Vuk; Karapandza, Rasa; Stojmirovic, Aleksandar; Pržulj, Nataša

    2014-04-01

    Sophisticated methods for analysing complex networks promise to be of great benefit to almost all scientific disciplines, yet they elude us. In this work, we make fundamental methodological advances to rectify this. We discover that the interaction between a small number of roles, played by nodes in a network, can characterize a network's structure and also provide a clear real-world interpretation. Given this insight, we develop a framework for analysing and comparing networks, which outperforms all existing ones. We demonstrate its strength by uncovering novel relationships between seemingly unrelated networks, such as Facebook, metabolic, and protein structure networks. We also use it to track the dynamics of the world trade network, showing that a country's role of a broker between non-trading countries indicates economic prosperity, whereas peripheral roles are associated with poverty. This result, though intuitive, has escaped all existing frameworks. Finally, our approach translates network topology into everyday language, bringing network analysis closer to domain scientists.

  9. CORRELATION PROFILES AND MOTIFS IN COMPLEX NETWORKS.

    Energy Technology Data Exchange (ETDEWEB)

    MASLOV,S.SNEPPEN,K.ALON,U.

    2004-01-16

    Networks have recently emerged as a unifying theme in complex systems research [1]. It is in fact no coincidence that networks and complexity are so heavily intertwined. Any future definition of a complex system should reflect the fact that such systems consist of many mutually interacting components. These components are far from being identical as say electrons in systems studied by condensed matter physics. In a truly complex system each of them has a unique identity allowing one to separate it from the others. The very first question one may ask about such a system is which other components a given component interacts with? This information system wide can be visualized as a graph, whose nodes correspond to individual components of the complex system in question and edges to their mutual interactions. Such a network can be thought of as a backbone of the complex system. Of course, system's dynamics depends not only on the topology of an underlying network but also on the exact form of interaction of components with each other, which can be very different in various complex systems. However, the underlying network may contain clues about the basic design principles and/or evolutionary history of the complex system in question. The goal of this article is to provide readers with a set of useful tools that would help to decide which features of a complex network are there by pure chance alone, and which of them were possibly designed or evolved to their present state.

  10. Epidemics and rumours in complex networks

    CERN Document Server

    Draief, Moez

    2009-01-01

    Information propagation through peer-to-peer systems, online social systems, wireless mobile ad hoc networks and other modern structures can be modelled as an epidemic on a network of contacts. Understanding how epidemic processes interact with network topology allows us to predict ultimate course, understand phase transitions and develop strategies to control and optimise dissemination. This book is a concise introduction for applied mathematicians and computer scientists to basic models, analytical tools and mathematical and algorithmic results. Mathematical tools introduced include coupling

  11. Socioeconomic development and stability: A complex network blueprint

    CERN Document Server

    Costa, L F

    2005-01-01

    The current work discusses how complex networks can be applied in order to aid economical development and stability at several scales and contexts. The following activities are involved: (a) compilation of several types of data related to socioeconomic development; (b) representation of such data in terms of multilayer interacting complex networks (cond-mat/0406369) registered geographically; (c) application of traditional and new methods for complex networks characterization and analysis. Such an approach allows the identification of bottlenecks and deficits/surpluses, simulation of system development under varying constraints and perturbations, as well as the application of optimization methods in order to help identify the most effective strategies leading to social and economic wealth and stability. In addition to its practical implications, such an approach also emphasizes several issues of substantial theoretical interest, including the integration of networks of different natures, the interplay between...

  12. Modelling, Estimation and Control of Networked Complex Systems

    CERN Document Server

    Chiuso, Alessandro; Frasca, Mattia; Rizzo, Alessandro; Schenato, Luca; Zampieri, Sandro

    2009-01-01

    The paradigm of complexity is pervading both science and engineering, leading to the emergence of novel approaches oriented at the development of a systemic view of the phenomena under study; the definition of powerful tools for modelling, estimation, and control; and the cross-fertilization of different disciplines and approaches. This book is devoted to networked systems which are one of the most promising paradigms of complexity. It is demonstrated that complex, dynamical networks are powerful tools to model, estimate, and control many interesting phenomena, like agent coordination, synchronization, social and economics events, networks of critical infrastructures, resources allocation, information processing, or control over communication networks. Moreover, it is shown how the recent technological advances in wireless communication and decreasing in cost and size of electronic devices are promoting the appearance of large inexpensive interconnected systems, each with computational, sensing and mobile cap...

  13. Critical Transitions in Social Network Activity

    CERN Document Server

    Kuehn, Christian; Romero, Daniel

    2013-01-01

    A large variety of complex systems in ecology, climate science, biomedicine and engineering have been observed to exhibit tipping points, where the internal dynamical state of the system abruptly changes. For example, such critical transitions may result in the sudden change of ecological environments and climate conditions. Data and models suggest that some of these drastic events may be preceded by detectable early-warning signs. This view is also corroborated by abstract mathematical theory for generic bifurcations in stochastic multi-scale systems. Whether early-warnings are also present in social networks that anticipate \\textit{a-priori unknown} events in society is an open problem to which only highly speculative answers can be given at present. Here, we focus on \\textit{a-priori known} events and analyze a social network data set with a focus on classical variance and autocorrelation warning signs. We find that several a-priori known events are preceded by variance and autocorrelation growth as predic...

  14. Synchronization of impulsively coupled complex networks

    Institute of Scientific and Technical Information of China (English)

    Sun Wen; Chen Zhong; Chen Shi-Hua

    2012-01-01

    We investigate the synchronization of complex networks,which are impulsively coupled only at discrete instants.Based on the comparison theory of impulsive differential systems,a distributed impulsive control scheme is proposed for complex dynamical networks to achieve synchronization.The proposed scheme not only takes into account the influence of all nodes to network synchronization,which depends on the weight of each node in the network,but also provides us with a flexible method to select the synchronized state of the network.In addition,it is unnecessary for the impulsive coupling matrix to be symmetrical.Finally,the proposed control scheme is applied to a chaotic Lorenz network and Chua's circuit network.Numerical simulations are used to illustrate the validity of this control scheme.

  15. Percolation of localized attack on complex networks

    CERN Document Server

    Shao, Shuai; Stanley, H Eugene; Havlin, Shlomo

    2014-01-01

    The robustness of complex networks against node failure and malicious attack has been of interest for decades, while most of the research has focused on random attack or hub-targeted attack. In many real-world scenarios, however, attacks are neither random nor hub-targeted, but localized, where a group of neighboring nodes in a network are attacked and fail. In this paper we develop a percolation framework to analytically and numerically study the robustness of complex networks against such localized attack. In particular, we investigate this robustness in Erd\\H{o}s-R\\'{e}nyi networks, random-regular networks, and scale-free networks. Our results provide insight into how to better protect networks, enhance cybersecurity, and facilitate the design of more robust infrastructures.

  16. Spreading paths in partially observed social networks

    CERN Document Server

    Onnela, Jukka-Pekka

    2011-01-01

    Understanding 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 path lengths 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, structurally realistic social network as a platform 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)? Alt...

  17. Loneliness, Social Networks, and Social Functioning in Borderline Personality Disorder.

    Science.gov (United States)

    Liebke, Lisa; Bungert, Melanie; Thome, Janine; Hauschild, Sophie; Gescher, Dorothee Maria; Schmahl, Christian; Bohus, Martin; Lis, Stefanie

    2016-08-08

    Persistent loneliness is often reported by patients with borderline personality disorder (BPD). However, empirical studies investigating this aspect of BPD psychopathology are sparse. Studies from social psychology revealed that social isolation and low social functioning contribute to loneliness, that is, the subjective feeling of being alone. The aim of the present study was to contribute to the understanding of loneliness in BPD by investigating its relation to social isolation and functioning in different domains of life. Subjective experience of loneliness was measured in 80 women (40 BPD patients, 40 healthy controls) with the UCLA Loneliness Scale. Social isolation and social functioning were assessed with the Social Network Inventory and the Social Functioning Scale. In addition, we assessed global functioning with the Global Assessment of Functioning. BPD patients reported stronger feelings of loneliness compared to healthy participants. In general, the level of loneliness was linked to network size, social engagement, and prosocial behavior. Diversity of social networks and functioning in the domain of interpersonal communication were associated with the level of loneliness only in BPD. A reduced variety of roles in social life together with impairments in interpersonal communication were particularly relevant for the experience of loneliness in BPD, suggesting an indirect path to target this psychopathological feature in therapeutic interventions. However, both social isolation and social functioning were not sufficient to explain the severely increased loneliness experienced by these patients, stressing the need for further investigation of determinants of loneliness in this clinical population. (PsycINFO Database Record

  18. 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.

  19. Scaling Up Connections: Everyday Cosmopolitanism, Complexity Theory & Social Capital

    Directory of Open Access Journals (Sweden)

    Jenny Onyx

    2011-11-01

    Full Text Available One of the key questions of contemporary society is how to foster and develop social interactions which will lead to a strong and inclusive society, one which accounts for the diversity inherent in local communities, whether that diversity be based on differences in interest or diversity in language and culture. The purpose of this paper is to examine three concepts which are used in the exploration of social interactions to suggest ways in which the interplay of these concepts might provide a richer understanding of social interactions. The three concepts are everyday cosmopolitanism, complexity theory and social capital. Each provides a partial approach to explanations of social interactions. Through focussing on social networking as a significant example of social interactions, we will demonstrate how the concepts can be linked and this linking brings potential for a clearer understanding of the processes through which this inclusive society may develop.

  20. Managing Complex Network Operation with Predictive Analytics

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Zhenyu; Wong, Pak C.; Mackey, Patrick S.; Chen, Yousu; Ma, Jian; Schneider, Kevin P.; Greitzer, Frank L.

    2008-03-26

    Complex networks play an important role in modern societies. Their failures, such as power grid blackouts, would lead to significant disruption of people’s life, industry and commercial activities, and result in massive economic losses. Operation of these complex networks is an extremely challenging task due to their complex structures, wide geographical coverage, complex data/information technology systems, and highly dynamic and nonlinear behaviors. None of the complex network operation is fully automated; human-in-the-loop operation is critical. Given the complexity involved, there may be thousands of possible topological configurations at any given time. During an emergency, it is not uncommon for human operators to examine thousands of possible configurations in near real-time to choose the best option and operate the network effectively. In today’s practice, network operation is largely based on experience with very limited real-time decision support, resulting in inadequate management of complex predictions and inability to anticipate, recognize, and respond to situations caused by human errors, natural disasters, and cyber attacks. A systematic approach is needed to manage the complex operation paradigms and choose the best option in a near-real-time manner. This paper applies predictive analytics techniques to establish a decision support system for complex network operation management and help operators to predict potential network failures and adapt the network to adverse situations. The resultant decision support system enables continuous monitoring of network performance and turns large amounts of data into actionable information. Examples with actual power grid data are presented to demonstrate the capability of this proposed decision support system.

  1. Anomaly detection in online social networks

    CERN Document Server

    Savage, David; Yu, Xinghuo; Chou, Pauline; Wang, Qingmai

    2016-01-01

    Anomalies in online social networks can signify irregular, and often illegal behaviour. Anomalies in online social networks can signify irregular, and often illegal behaviour. Detection of such anomalies has been used to identify malicious individuals, including spammers, sexual predators, and online fraudsters. In this paper we survey existing computational techniques for detecting anomalies in online social networks. We characterise anomalies as being either static or dynamic, and as being labelled or unlabelled, and survey methods for detecting these different types of anomalies. We suggest that the detection of anomalies in online social networks is composed of two sub-processes; the selection and calculation of network features, and the classification of observations from this feature space. In addition, this paper provides an overview of the types of problems that anomaly detection can address and identifies key areas of future research.

  2. 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...

  3. 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.

  4. 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......It has recently become possible to record detailed social interactions in large social systems with high resolution. As we study these datasets, human social interactions display patterns that emerge at multiple time scales, from minutes to months. On a fundamental level, understanding...... is difficult and expensive. Here, we consider the dynamic network of proximity-interactions between approximately 500 individuals participating in the Copenhagen Networks Study. We show that in order to accurately model spreading processes in the network, the dynamic processes that occur on the order...

  5. 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...... will experience changes through this phenomenon in the future. This empirical study investigates the types of content that is communicated for different brands and industries in leading Social Media portals on the German market in 2011. It turns out that this kind of CSR communication differs in terms of portals...

  6. 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...... will experience changes through this phenomenon in the future. This empirical study investigates the types of content that is communicated for different brands and industries in leading Social Media portals on the German market in 2011. It turns out that this kind of CSR communication differs in terms of portals...

  7. Optimization of spatial complex networks

    Science.gov (United States)

    Guillier, S.; Muñoz, V.; Rogan, J.; Zarama, R.; Valdivia, J. A.

    2017-02-01

    First, we estimate the connectivity properties of a predefined (fixed node locations) spatial network which optimizes a connectivity functional that balances construction and transportation costs. In this case we obtain a Gaussian distribution for the connectivity. However, when we consider these spatial networks in a growing process, we obtain a power law distribution for the connectivity. If the transportation costs in the functional involve the shortest geometrical path, we obtain a scaling exponent γ = 2.5. However, if the transportation costs in the functional involve just the shortest path, we obtain γ = 2.2. Both cases may be useful to analyze in some real networks.

  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. 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.

  10. The international entrepreneurial firms' social networks

    Directory of Open Access Journals (Sweden)

    Manuel Portugal Ferreira

    Full Text Available This paper investigates theoretically the importance and impact of the international entrepreneurial firms' (IEFs social networks on selected firms' strategies. We focus specifically on some core attributes of IEFs and the impact of social networks on such strategies as the choice of the foreign markets to operate and the foreign entry modes. The social networks are a major driver of the internationalization from inception and help in overcoming a variety of physical and social resource limitations as well as transactional hazards. We conclude that it is likely that both some fundamental characteristics of the IEFs and those of the foreign markets entered account for these firms reliance on their social networks.

  11. 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.

  12. Social network sampling using spanning trees

    Science.gov (United States)

    Jalali, Zeinab S.; Rezvanian, Alireza; Meybodi, Mohammad Reza

    2016-12-01

    Due to the large scales and limitations in accessing most online social networks, it is hard or infeasible to directly access them in a reasonable amount of time for studying and analysis. Hence, network sampling has emerged as a suitable technique to study and analyze real networks. The main goal of sampling online social networks is constructing a small scale sampled network which preserves the most important properties of the original network. In this paper, we propose two sampling algorithms for sampling online social networks using spanning trees. The first proposed sampling algorithm finds several spanning trees from randomly chosen starting nodes; then the edges in these spanning trees are ranked according to the number of times that each edge has appeared in the set of found spanning trees in the given network. The sampled network is then constructed as a sub-graph of the original network which contains a fraction of nodes that are incident on highly ranked edges. In order to avoid traversing the entire network, the second sampling algorithm is proposed using partial spanning trees. The second sampling algorithm is similar to the first algorithm except that it uses partial spanning trees. Several experiments are conducted to examine the performance of the proposed sampling algorithms on well-known real networks. The obtained results in comparison with other popular sampling methods demonstrate the efficiency of the proposed sampling algorithms in terms of Kolmogorov-Smirnov distance (KSD), skew divergence distance (SDD) and normalized distance (ND).

  13. Social networking among upper extremity patients.

    Science.gov (United States)

    Rozental, Tamara D; George, Tina M; Chacko, Aron T

    2010-05-01

    Despite their rising popularity, the health care profession has been slow to embrace social networking sites. These are Web-based initiatives, designed to bring people with common interests or activities under a common umbrella. The purpose of this study is to evaluate social networking patterns among upper extremity patients. A total of 742 anonymous questionnaires were distributed among upper extremity outpatients, with a 62% response rate (462 were completed). Demographic characteristics (gender, age, level of education, employment, type of health insurance, and income stratification) were defined, and data on computer ownership and frequency of social networking use were collected. Social network users and nonusers were compared according to their demographic and socioeconomic characteristics. Our patient cohort consisted of 450 patients. Of those 450 patients, 418 had a high school education or higher, and 293 reported a college or graduate degree. The majority of patients (282) were employed at the time of the survey, and income was evenly distributed among U.S. Census Bureau quintiles. A total of 349 patients reported computer ownership, and 170 reported using social networking sites. When compared to nonusers, social networking users were younger (pnetworking use. Most users (n = 114) regularly visit a single site. Facebook was the most popular site visited (n=142), followed by MySpace (n=28) and Twitter (n=16). Of the 450 upper extremity patients in our sample, 170 use social networking sites. Younger age, higher level of education, and computer ownership were associated with social networking use. Physicians should consider expanding their use of social networking sites to reach their online patient populations. Copyright 2010 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

  14. Link Prediction in Complex Networks: A Survey

    CERN Document Server

    Lu, Linyuan

    2010-01-01

    Link prediction in complex networks has attracted increasing attention from both physical and computer science communities. The algorithms can be used to extract missing information, identify spurious interactions, evaluate network evolving mechanisms, and so on. This article summaries recent progress about link prediction algorithms, emphasizing on the contributions from physical perspectives and approaches, such as the random-walk-based methods and the maximum likelihood methods. We also introduce three typical applications: reconstruction of networks, evaluation of network evolving mechanism and classification of partially labelled networks. Finally, we introduce some applications and outline future challenges of link prediction algorithms.

  15. Universality in complex networks: random matrix analysis.

    Science.gov (United States)

    Bandyopadhyay, Jayendra N; Jalan, Sarika

    2007-08-01

    We apply random matrix theory to complex networks. We show that nearest neighbor spacing distribution of the eigenvalues of the adjacency matrices of various model networks, namely scale-free, small-world, and random networks follow universal Gaussian orthogonal ensemble statistics of random matrix theory. Second, we show an analogy between the onset of small-world behavior, quantified by the structural properties of networks, and the transition from Poisson to Gaussian orthogonal ensemble statistics, quantified by Brody parameter characterizing a spectral property. We also present our analysis for a protein-protein interaction network in budding yeast.

  16. Competitive Dynamics on Complex Networks

    CERN Document Server

    Zhao, Jiuhua; Wang, Xiaofan

    2014-01-01

    We consider a dynamical network model in which two competitors have fixed and different states, and each normal agent adjusts its state according to a distributed consensus protocol. The state of each normal agent converges to a steady value which is a convex combination of the competitors' states, and is independent of the initial states of agents. This implies that the competition result is fully determined by the network structure and positions of competitors in the network. We compute an Influence Matrix (IM) in which each element characterizing the influence of an agent on another agent in the network. We use the IM to predict the bias of each normal agent and thus predict which competitor will win. Furthermore, we compare the IM criterion with seven node centrality measures to predict the winner. We find that the competitor with higher Katz Centrality in an undirected network or higher PageRank in a directed network is much more likely to be the winner. These findings may shed new light on the role of n...

  17. The Dynamics of Coalition Formation on Complex Networks

    Science.gov (United States)

    Auer, S.; Heitzig, J.; Kornek, U.; Schöll, E.; Kurths, J.

    2015-08-01

    Complex networks describe the structure of many socio-economic systems. However, in studies of decision-making processes the evolution of the underlying social relations are disregarded. In this report, we aim to understand the formation of self-organizing domains of cooperation (“coalitions”) on an acquaintance network. We include both the network’s influence on the formation of coalitions and vice versa how the network adapts to the current coalition structure, thus forming a social feedback loop. We increase complexity from simple opinion adaptation processes studied in earlier research to more complex decision-making determined by costs and benefits, and from bilateral to multilateral cooperation. We show how phase transitions emerge from such coevolutionary dynamics, which can be interpreted as processes of great transformations. If the network adaptation rate is high, the social dynamics prevent the formation of a grand coalition and therefore full cooperation. We find some empirical support for our main results: Our model develops a bimodal coalition size distribution over time similar to those found in social structures. Our detection and distinguishing of phase transitions may be exemplary for other models of socio-economic systems with low agent numbers and therefore strong finite-size effects.

  18. 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...... induces different career choices for individuals from different social groups. This further translates into stable occupational segregation equilibria in the labor market. We derive the conditions for wage and unemployment inequality in the segregation equilibria and characterize first and second best...

  19. 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.

  20. Critical Transitions in Social Network Activity

    DEFF Research Database (Denmark)

    Kuehn, Christian; Martens, Erik Andreas; Romero, Daniel M

    2014-01-01

    a priori known events are preceded by variance and autocorrelation growth. Our findings thus clearly establish the necessary starting point to further investigate the relationship between abstract mathematical theory and various classes of critical transitions in social networks.......A large variety of complex systems in ecology, climate science, biomedicine and engineering have been observed to exhibit tipping points, where the dynamical state of the system abruptly changes. For example, such critical transitions may result in the sudden change of ecological environments...... and climate conditions. Data and models suggest that detectable warning signs may precede some of these drastic events. This view is also corroborated by abstract mathematical theory for generic bifurcations in stochastic multi-scale systems. Whether such stochastic scaling laws used as warning signs...