Community Detection in Multi-Layer Networks

In the scope of the current thesis we review and analyse networks that are formed by nodes with several attributes. We suppose that different layers of communities are embedded in such networks, besides each of the layers is connected with nodes' attributes. For example, examine one of a variety of online social networks: an user participates in a plurality of different groups/communities – schoolfellows, colleagues, clients, etc. We introduce a detection algorithm for the above-mentioned communities. Normally the result of the detection is the community supplemented just by the most dominant attribute, disregarding others. We propose an algorithm that bypasses dominant communities and detects communities which are formed by other nodes' attributes. We also review formation models of the attributed networks and present a Human Communication Network (HCN) model. We introduce a High School Texting Network (HSTN) and examine our methods for that network.

Management of social networks in the educational process

The research developed in this work consists in proposing a set of techniques for management of social networks and their integration into the educational process. The proposals made are based on assumptions that have been proven with simple examples in a real scenario of university teaching. The results show that social networks have more capacity to spread information than educational web platforms. Moreover, educational social networks are developed in a context of freedom of expression intrinsically linked to Internet freedom. In that context, users can write opinions or comments which are not liked by the staff of schools. However, this feature can be exploited to enrich the educational process and improve the quality of their achievement. The network has covered needs and created new ones. So, the figure of the Community Manager is proposed as agent in educational context for monitoring network and aims to channel the opinions and to provide a rapid response to an academic problem.

MODULARITY BASED FUZZY COMMUNITY DETECTION IN SOCIAL NETWORKS

Fuzzy community detection is to identify fuzzy communities in a network, which are groups of vertices in the network such that the membership of a vertex in one community is in [0,1] and that the sum of memberships of vertices in all communities equals to 1. Fuzzy communities are pervasive in social networks, but only a few works have been done for fuzzy community detection. Recently, a one-step forward extension of Newman’s Modularity, the most popular quality function for disjoint community detection, results into the Generalized Modularity (GM) that demonstrates good performance in finding well-known fuzzy communities. Thus, GMis chosen as the quality function in our research. We first propose a generalized fuzzy t-norm modularity to investigate the effect of different fuzzy intersection operators on fuzzy community detection, since the introduction of a fuzzy intersection operation is made feasible by GM. The experimental results show that the Yager operator with a proper parameter value performs better than the product operator in revealing community structure. Then, we focus on how to find optimal fuzzy communities in a network by directly maximizing GM, which we call it Fuzzy Modularity Maximization (FMM) problem. The effort on FMM problem results into the major contribution of this thesis, an efficient and effective GM-based fuzzy community detection method that could automatically discover a fuzzy partition of a network when it is appropriate, which is much better than fuzzy partitions found by existing fuzzy community detection methods, and a crisp partition of a network when appropriate, which is competitive with partitions resulted from the best disjoint community detections up to now. We address FMM problem by iteratively solving a sub-problem called One-Step Modularity Maximization (OSMM). We present two approaches for solving this iterative procedure: a tree-based global optimizer called Find Best Leaf Node (FBLN) and a heuristic-based local optimizer. The OSMM problem is based on a simplified quadratic knapsack problem that can be solved in linear time; thus, a solution of OSMM can be found in linear time. Since the OSMM algorithm is called within FBLN recursively and the structure of the search tree is non-deterministic, we can see that the FMM/FBLN algorithm runs in a time complexity of at least O (n2). So, we also propose several highly efficient and very effective heuristic algorithms namely FMM/H algorithms. We compared our proposed FMM/H algorithms with two state-of-the-art community detection methods, modified MULTICUT Spectral Fuzzy c-Means (MSFCM) and Genetic Algorithm with a Local Search strategy (GALS), on 10 real-world data sets. The experimental results suggest that the H2 variant of FMM/H is the best performing version. The H2 algorithm is very competitive with GALS in producing maximum modularity partitions and performs much better than MSFCM. On all the 10 data sets, H2 is also 2-3 orders of magnitude faster than GALS. Furthermore, by adopting a simply modified version of the H2 algorithm as a mutation operator, we designed a genetic algorithm for fuzzy community detection, namely GAFCD, where elite selection and early termination are applied. The crossover operator is designed to make GAFCD converge fast and to enhance GAFCD’s ability of jumping out of local minimums. Experimental results on all the data sets show that GAFCD uncovers better community structure than GALS.

Community analysis in dynamic social networks

Magdeburg, Univ., Fak. für Informatik, Diss., 2009

A cold blizzard was raging, but the light shone brightly' : social networks presented in stained glass within an industrial community

Historical stained glass in Calumet and Laurium revealed the complex structures of these industrial communities. Creating an Industrial Archaeology-focused approach, I examined stained glass as material culture. Sacred glass revealed ethnic and religious values of a congregation through the style, iconography, and quality of the glasswork. Residential glass showed how owners represented themselves within cultural settings by meeting social expectations. Commercial glass indicated community status of owners through discreet and artistic shows of wealth and taste. Corporate glass displayed prosperity and belonging through the superior quality and cost of the glasswork. Viewing stained glass as material culture opened new methods of looking at both stained glass and industrial communities. Findings from my research can teach the public about the importance of preserving and conserving stained glass, and that can lead to greater public appreciation for the material culture found within these industrial communities.

Feature analysis of spammers in social networks with active honeypots:a case study of Chinese microblogging networks

In this poster we presented our preliminary work on the study of spammer detection and analysis with 50 active honeypot profiles implemented on Weibo.com and QQ.com microblogging networks. We picked out spammers from legitimate users by manually checking every captured user's microblogs content. We built a spammer dataset for each social network community using these spammer accounts and a legitimate user dataset as well. We analyzed several features of the two user classes and made a comparison on these features, which were found to be useful to distinguish spammers from legitimate users. The followings are several initial observations from our analysis on the features of spammers captured on Weibo.com and QQ.com. ¦The following/follower ratio of spammers is usually higher than legitimate users. They tend to follow a large amount of users in order to gain popularity but always have relatively few followers. ¦There exists a big gap between the average numbers of microblogs posted per day from these two classes. On Weibo.com, spammers post quite a lot microblogs every day, which is much more than legitimate users do; while on QQ.com spammers post far less microblogs than legitimate users. This is mainly due to the different strategies taken by spammers on these two platforms. ¦More spammers choose a cautious spam posting pattern. They mix spam microblogs with ordinary ones so that they can avoid the anti-spam mechanisms taken by the service providers. ¦Aggressive spammers are more likely to be detected so they tend to have a shorter life while cautious spammers can live much longer and have a deeper influence on the network. The latter kind of spammers may become the trend of social network spammer. © 2012 IEEE.

Cultural self-identification(s) and personal social networks among first and second-generation immigrants

L’estudi examina les relacions entre (1) les xarxes socials personals de la població immigrant resident a Barcelona i (2) les seves identitats culturals múltiples. L’objectiu principal de l’estudi és entendre com el contingut i l’estructura de les relacions socials dels immigrants facilita o dificulta (1) tenir un sentiment de pertinença a les noves cultures d’acollida, la catalana i la espanyola, i (2) la integració d’aquestes noves identitats socioculturals amb la seva identitat d’origen en una nova identitat bicultural cohesiva. El nostre plantejament inicial era que els immigrants amb xarxes socials més diverses des del punt de vista de la seva composició cultural tindrien més recursos socials i experiències cognitives més diverses , factors que afavoreixen les identificacions múltiples i la participació cívica. Els resultats de l’estudi mostren que el grau d’identificació dels participants amb la seva cultura ètnica o d’origen és força alt i, en certa mesura, més alt en comparació amb les cultures d’acollida ( catalana, cívica i espanyola). Tanmateix, el vincle dels participants amb les cultures d’acollida (p. ex., la cultura catalana) és prou rellevant per a indicar una orientació bicultural (catalana i ètnica). Les anàlisis de correlacions revelen que sentir-se català no impedeix sentir-se part de la comunitat etnocultural d’origen. A més, existeix una interrelació entre l'orientació cultural catalana i la identificació amb les comunitats cíviques locals. De la mateixa manera, tenir competències en llengua catalana no va en detriment de les competències en llengua castellana. Les anàlisis també mostren que factors com l’orientació cultural catalana, l’ús del català i la identificació amb la cultura catalana tenen una correlació positiva amb el grau de chohesio de la indentitat bicultural, afavoreixen el benestar psicològic i disminueixen l’estrès aculturatiu. L’anàlisi de les xarxes socials mostra que la identificació amb la cultura catalana, l’orientació cultural catalana i la integració de la identitat són factors clau per tenir xarxes socials més diverses des del punt de vista ètnic i lingüístic, amb menys membres del col•lectiu d’origen, i amb subgrups o “cliques” culturalment més heterogenis. La identificació espanyola també prediu, en mesura més reduïda, la diversitat de les xarxes. Els nostres resultats contribueixen a la recerca actual i les teories sobre interculturalitat i identitat cultural.

Evolution of Coordination in Social Networks: A Numerical Study

Coordination games are important to explain efficient and desirable social behavior. Here we study these games by extensive numerical simulation on networked social structures using an evolutionary approach. We show that local network effects may promote selection of efficient equilibria in both pure and general coordination games and may explain social polarization. These results are put into perspective with respect to known theoretical results. The main insight we obtain is that clustering, and especially community structure in social networks has a positive role in promoting socially efficient outcomes.

Use of social networks for academic purposes: a case study

Purpose This paper aims to analyse various aspects of an academic social network: the profile of users, the reasons for its use, its perceived benefits and the use of other social media for scholarly purposes. Design/methodology/approach The authors examined the profiles of the users of an academic social network. The users were affiliated with 12 universities. The following were recorded for each user: sex, the number of documents uploaded, the number of followers, and the number of people being followed. In addition, a survey was sent to the individuals who had an email address in their profile. Findings Half of the users of the social network were academics and a third were PhD students. Social sciences scholars accounted for nearly half of all users. Academics used the service to get in touch with other scholars, disseminate research results and follow other scholars. Other widely employed social media included citation indexes, document creation, edition and sharing tools and communication tools. Users complained about the lack of support for the utilisation of these tools. Research limitations/implications The results are based on a single case study. Originality/value This study provides new insights on the impact of social media in academic contexts by analysing the user profiles and benefits of a social network service that is specifically targeted at the academic community.

Use of social networks for academic purposes: a case study

Purpose- This paper aims to analyse various aspects of an academic social network: the profile of users, the reasons for its use, its perceived benefits and the use of other social media for scholarly purposes. Design/methodology/approach- The authors examined the profiles of the users of an academic social network. The users were affiliated with 12 universities. The following were recorded for each user: sex, the number of documents uploaded, the number of followers, and the number of people being followed. In addition, a survey was sent to the individuals who had an email address in their profile. Findings- Half of the users of the social network were academics and a third were PhD students. Social sciences scholars accounted for nearly half of all users. Academics used the service to get in touch with other scholars, disseminate research results and follow other scholars. Other widely employed social media included citation indexes, document creation, edition and sharing tools and communication tools. Users complained about the lack of support for the utilisation of these tools. Research limitations/implications- The results are based on a single case study. Originality/value- This study provides new insights on the impact of social media in academic contexts by analysing the user profiles and benefits of a social network service that is specifically targeted at the academic community.

Relatedness in Evidence Networks

Einhergehend mit der Entwicklung und zunehmenden Verfügbarkeit des Internets hat sich die Art der Informationsbereitstellung und der Informationsbeschaffung deutlich geändert. Die einstmalige Trennung zwischen Publizist und Konsument wird durch kollaborative Anwendungen des sogenannten Web 2.0 aufgehoben, wo jeder Teilnehmer gleichsam Informationen bereitstellen und konsumieren kann. Zudem können Einträge anderer Teilnehmer erweitert, kommentiert oder diskutiert werden. Mit dem Social Web treten schließlich die sozialen Beziehungen und Interaktionen der Teilnehmer in den Vordergrund. Dank mobiler Endgeräte können zu jeder Zeit und an nahezu jedem Ort Nachrichten verschickt und gelesen werden, neue Bekannschaften gemacht oder der aktuelle Status dem virtuellen Freundeskreis mitgeteilt werden. Mit jeder Aktivität innerhalb einer solchen Applikation setzt sich ein Teilnehmer in Beziehung zu Datenobjekten und/oder anderen Teilnehmern. Dies kann explizit geschehen, indem z.B. ein Artikel geschrieben wird und per E-Mail an Freunde verschickt wird. Beziehungen zwischen Datenobjekten und Nutzern fallen aber auch implizit an, wenn z.B. die Profilseite eines anderen Teilnehmers aufgerufen wird oder wenn verschiedene Teilnehmer einen Artikel ähnlich bewerten. Im Rahmen dieser Arbeit wird ein formaler Ansatz zur Analyse und Nutzbarmachung von Beziehungsstrukturen entwickelt, welcher auf solchen expliziten und impliziten Datenspuren aufbaut. In einem ersten Teil widmet sich diese Arbeit der Analyse von Beziehungen zwischen Nutzern in Applikationen des Social Web unter Anwendung von Methoden der sozialen Netzwerkanalyse. Innerhalb einer typischen sozialen Webanwendung haben Nutzer verschiedene Möglichkeiten zu interagieren. Aus jedem Interaktionsmuster werden Beziehungsstrukturen zwischen Nutzern abgeleitet. Der Vorteil der impliziten Nutzer-Interaktionen besteht darin, dass diese häufig vorkommen und quasi nebenbei im Betrieb des Systems abfallen. Jedoch ist anzunehmen, dass eine explizit angegebene Freundschaftsbeziehung eine stärkere Aussagekraft hat, als entsprechende implizite Interaktionen. Ein erster Schwerpunkt dieser Arbeit ist entsprechend der Vergleich verschiedener Beziehungsstrukturen innerhalb einer sozialen Webanwendung. Der zweite Teil dieser Arbeit widmet sich der Analyse eines der weit verbreitetsten Profil-Attributen von Nutzern in sozialen Webanwendungen, dem Vornamen. Hierbei finden die im ersten Teil vorgestellten Verfahren und Analysen Anwendung, d.h. es werden Beziehungsnetzwerke für Namen aus Daten von sozialen Webanwendungen gewonnen und mit Methoden der sozialen Netzwerkanalyse untersucht. Mithilfe externer Beschreibungen von Vornamen werden semantische Ähnlichkeiten zwischen Namen bestimmt und mit jeweiligen strukturellen Ähnlichkeiten in den verschiedenen Beziehungsnetzwerken verglichen. Die Bestimmung von ähnlichen Namen entspricht in einer praktischen Anwendung der Suche von werdenden Eltern nach einem passenden Vornamen. Die Ergebnisse zu der Analyse von Namensbeziehungen sind die Grundlage für die Implementierung der Namenssuchmaschine Nameling, welche im Rahmen dieser Arbeit entwickelt wurde. Mehr als 35.000 Nutzer griffen innerhalb der ersten sechs Monate nach Inbetriebnahme auf Nameling zu. Die hierbei anfallenden Nutzungsdaten wiederum geben Aufschluss über individuelle Vornamenspräferenzen der Anwender. Im Rahmen dieser Arbeit werden diese Nutzungsdaten vorgestellt und zur Bestimmung sowie Bewertung von personalisierten Vornamensempfehlungen verwendet. Abschließend werden Ansätze zur Diversifizierung von personalisierten Vornamensempfehlungen vorgestellt, welche statische Beziehungsnetzwerke für Namen mit den individuellen Nutzungsdaten verknüpft.

Motivations for knowledge sharing in virtual social networks: a comparative study between Brazil and France

Sociedades pós-modernas caracterizam-se pela transição de economias baseadas em ativos tangíveis para economias de conhecimento, onde indivíduos vivenciam uma imprescindível conectividade, mas ao mesmo tempo, experimentam um enfraquecimento das estruturas sociais, que tem generado uma crescente necessidade de se criar bases cognitivas e afetivas para a vida (Rheingold, 1992; Wasko & Farah, 2005; Arvidsson, 2008). Nesse cenário se desenvolve o fenômeno das redes sociais virtuais, agregando milhões de pessoas que compartilham mensagens de texto, imagens e vídeos todos os dias (Nielsen, 2012) fazendo com que organizações privadas foquem cada vez mais seus investimentos para acompanhar as novas tendências (McWilliam, 2000; Reichheld & Schefter, 2000; Yoo, Suh & Lee, 2002; Arvidsson, 2008). Consequentemente, uma das mais importantes questões que vem ganhando importância no meio academico e entre profissionais da área é justamente: por que as pessoas compartilham conhecimento online? (Monge, Fulk, Kalman, Flanigan, Parnassa & Rumsey, 1998; Lin, 2001) Por meio de uma metodologia de estudo de caso conduzida no Brasil e na França, este estudo objetiva produzir uma relevante revisão teórica acerca do tema, trazendo novas idéias de diferentes contextos, e propondo um modelo para avaliar as principais motivações que conduzem indivíduos a compartilhar conhecimento em redes sociais virtuais. Essas razões foram estruturadas em cinco dimensões: capital estrutural, cognitivo e relacional, motivações pessoais e razões monetárias (Nahapiet & Ghoshal, 1998; Wasko & Faraj, 2005; Chiu et al, 2006). As evidências sugerem que o processo de participar e compartilhar conhecimento em redes sociais virtuais é resultado de uma complexa combinação de motivações de orientação pessoal e coletiva, que parecem variar pouco de acordo com os diferentes objetivos e contextos dessas comunidades, onde as razões financeiras parecem ser secundárias.

Using Amino Acid Correlation and Community Detection Algorithms to Identify Functional Determinants in Protein Families

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

QK-Means: A clustering technique based on community detection and K-Means for deployment of cluster head nodes

Wireless Sensor Networks (WSN) are a special kind of ad-hoc networks that is usually deployed in a monitoring field in order to detect some physical phenomenon. Due to the low dependability of individual nodes, small radio coverage and large areas to be monitored, the organization of nodes in small clusters is generally used. Moreover, a large number of WSN nodes is usually deployed in the monitoring area to increase WSN dependability. Therefore, the best cluster head positioning is a desirable characteristic in a WSN. In this paper, we propose a hybrid clustering algorithm based on community detection in complex networks and traditional K-means clustering technique: the QK-Means algorithm. Simulation results show that QK-Means detect communities and sub-communities thus lost message rate is decreased and WSN coverage is increased. © 2012 IEEE.

Disentangling social networks from spatiotemporal dynamics: the temporal structure of a dolphin society

Social networks are static illustrations of dynamic societies, within which social interactions are constantly changing. Fundamental sources of variation include ranging behaviour and temporal demographic changes. Spatiotemporal dynamics can favour or limit opportunities for individuals to interact, and then a network may not essentially represent social processes. We examined whether a social network can embed such nonsocial effects in its topology, whereby emerging modules depict spatially or temporally segregated individuals. To this end, we applied a combination of spatial, temporal and demographic analyses to a long-term study of the association patterns of Guiana dolphins, Sotalia guianensis. We found that association patterns are organized into a modular social network. Space use was unlikely to reflect these modules, since dolphins' ranging behaviour clearly overlapped. However, a temporal demographic turnover, caused by the exit/entrance of individuals (most likely emigration/immigration), defined three modules of associations occurring at different times. Although this factor could mask real social processes, we identified the temporal scale that allowed us to account for these demographic effects. By looking within this turnover period (32 months), we assessed fission-fusion dynamics of the poorly known social organization of Guiana dolphins. We highlight that spatiotemporal dynamics can strongly influence the structure of social networks. Our findings show that hypothetical social units can emerge due to the temporal opportunities for individuals to interact. Therefore, a thorough search for a satisfactory spatiotemporal scale that removes such nonsocial noise is critical when analysing a social system. (C) 2012 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.