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A Framework for Analyzing Dynamic Social Networks

Full Text: ASNA10.pdf PDF

Social network analysis has emerged as a set of methods for the analysis of social structures and uncovering the patterning of interactions among the entities. In the past, social network analysis was mainly a static investigation by considering independent graphs at different snapshots or one aggregated graph over the time period. However, for the dynamic social networks that change over time, the static analysis misses the opportunity to capture evolutionary patterns. A community is one of these patterns, and it is affected by changes in the underlying population in the dynamic social networks. In the literature there has been a considerable amount of work done to detect communities in social networks. However, the communities are independently detected at each snapshot regardless of the structural relationship between consecutive snapshots. In this paper we present a framework for modeling and detecting community evolution in social networks. This framework allows tracking of events related to communities as well as events related to individual nodes. These events can be considered as building blocks for pattern detection in networks with evolving communities. We illustrate the capabilities and potential of our framework by applying it to a real dataset consisting of emails from the Enron Corporation. The evolution of the Enron communities is detected with the events defined in our framework.

Citation

M. Takaffoli, F. Sangi, J. Fagnan, O. Zaiane. "A Framework for Analyzing Dynamic Social Networks". Conference on Applications of Social Network Analysis, Zurich, Switzerland, pp 122-123, September 2010.

Keywords:  
Category: In Conference

BibTeX

@incollection{Takaffoli+al:ASNA10,
  author = {Mansoureh Takaffoli and Farzad Sangi and Justin Fagnan and Osmar R.
    Zaiane},
  title = {A Framework for Analyzing Dynamic Social Networks},
  Pages = {122-123},
  booktitle = {Conference on Applications of Social Network Analysis},
  year = 2010,
}

Last Updated: January 15, 2020
Submitted by Sabina P

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