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Please use this identifier to cite or link to this item: http://hdl.handle.net/1860/1596

Title: Visualizing the evolution of social networks
Authors: Zhu, Weizhong
Chen, Chaomei
Allen, Robert B.
Issue Date: 20-Apr-2006
Publisher: Drexel University. College of Information Science and Technology.
Series/Report no.: IST Research Day 2006 posters
Abstract: We are particularly interested in how a social network evolves over time. We construct social networks as follows. Vertices in a network represent individuals. Interrelationships between these individuals include a wide variety of types, for instance, exchanging emails and appearing in the same news. The strengths of such interrelationships are represented as edges. The evolution of a social network over a period of time, ranging from days in networks derived from news to years in networks associated with a working group, is studied by studying network snapshots taken from a series of consecutive time intervals within the entire period of time. Participating actors in the network are clustered and weighted based on attributes such as email send-reply pairs, interaction thread, and time-based centrality measures. We demonstrate two examples of how emergent linkage patterns can be identified so as to improve our understanding of the social dynamics of the underlying group. One example is based on an email archive of a working group; the other is based on a set of synthesized news data. For example, one may want to find out the most active group member through email conversations during a given period. We will demonstrate how our approach can help not only to understand the roles of actors in terms of their influence and contributions in social networks, but also to generate hypotheses and evidence for visual analytics.
URI: http://hdl.handle.net/1860/1596
Appears in Collections:Research Day Posters (IST)

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