Feedback effects between similarity and social influence in online communities

Crandall, David J.; Cosley, Dan; Huttenlocher, Daniel P.; Kleinberg, Jon; Suri, Siddharth

doi:10.1145/1401890.1401914

Cited by 515 publications

(367 citation statements)

References 22 publications

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“…To what extent, quantitatively, could semantic proximity predict, dynamically, the likelihood of coauthoring papers, or citing others? This comes to quantitatively determine homophilic processes (as in Fienberg and Wasserman, 1981;Lazega and van Duijn, 1997, for instance), yet in a co-evolving framework: here, semantic features jointly evolve with the successive reconfigurations of the social structure and agent semantic profiles (Roth, 2005;Crandall et al, 2008).…”

Section: Local Semantic Cohesivenessmentioning

confidence: 99%

Social and semantic coevolution in knowledge networks

2010

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Socio-semantic networks involve agents creating and processing information: communities of scientists, software developers, wiki contributors and webloggers are, among others, examples of such knowledge networks. We aim at demonstrating that the dynamics of these communities can be adequately described as the coevolution of a social and a socio-semantic network. More precisely, we will first introduce a theoretical framework based on a social network and a socio-semantic network, i.e. an epistemic network featuring agents, concepts and links between agents and between agents and concepts. Adopting a relevant empirical protocol, we will then describe the joint dynamics of social and socio-semantic structures, at both macroscopic and microscopic scales, emphasizing the remarkable stability of these macroscopic properties in spite of a vivid local, agentbased network dynamics.

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Section: Local Semantic Cohesivenessmentioning

confidence: 99%

Social and semantic coevolution in knowledge networks

2010

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“…The interplay between the phenomenons of social influence and social preference based on similarity between the editors in the context of open collaboration in Wikipedia is studied in Crandall et al (2008). The results indicate that both phenomenons play an important role in explaining the open collaboration patterns.…”

Section: Related Workmentioning

confidence: 99%

Diversity of editors and teams versus quality of cooperative work: experiments on wikipedia

2016

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We study whether and how the diversity of editors and teams affects the quality of work in a virtual cooperative work environment on the Wikipedia example. We propose a measure of interests diversity of an editor and some measures of team diversity in terms of members' interests and experience. Statistical and machine learning methods are used to investigate the dependency between diversity and work quality. The presented experimental results confirm our hypothesis that interest diversity of a single editors and team diversity are positively related to the quality of their work. Interestingly, some of our experiments also indicate that diversity may be more important than such attributes as productivity of an editor or size or experience of the team. Our experimental results demonstrate that it is possible to predict work quality based on diversity which is an additional statistical signal that diversity is correlated with work quality.

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“…A basic question here is to separate out the dual forces by which similarity promotes friendship (because people seek out others like them) and by which friendship correspondingly promotes similarity (because people are influenced by their friends). Recent work has used Web data in which both relationships and behaviour can be observed over time to understand how changes in similarity and changes in social links interact [18][19][20][21]; this is an ongoing research challenge where these forms of time-resolved data at large scales have the potential to play a significant role. …”

Section: Forming Ties and Joining Groupsmentioning

confidence: 99%

Analysis of large-scale social and information networks

Kleinberg

2013

Phil. Trans. R. Soc. A.

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The growth of the Web has required us to think about the design of information systems in which large-scale computational and social feedback effects are simultaneously at work. At the same time, the data generated by Web-scale systems—recording the ways in which millions of participants create content, link information, form groups and communicate with one another—have made it possible to evaluate long-standing theories of social interaction, and to formulate new theories based on what we observe. These developments have created a new level of interaction between computing and the social sciences, enriching the perspectives of both of these disciplines. We discuss some of the observations, theories and conclusions that have grown from the study of Web-scale social interaction, focusing on issues including the mechanisms by which people join groups, the ways in which different groups are linked together in social networks and the interplay of positive and negative interactions in these networks.

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Feedback effects between similarity and social influence in online communities

Cited by 515 publications

References 22 publications

Social and semantic coevolution in knowledge networks

Social and semantic coevolution in knowledge networks

Diversity of editors and teams versus quality of cooperative work: experiments on wikipedia

Analysis of large-scale social and information networks

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