Extracting scoial networks from instant messaging populations

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Title: Extracting scoial networks from instant messaging populations
Author: Resig, John; Dawara, Santosh; Homan, Christopher; Teredesai, Ankur
Abstract: In the analysis of large-scale social networks, a central problem is how to discover how members of the network to be analyzed are related. Instant messaging (IM) is a popular and relatively new form of social networks. An obvious barrier to such a study is that there is no de facto measure for how closely any pair of members of such a community are associated to describe the link information. We introduce several such measures in this paper.These proposed measures are obtained solely from the status pairs of IM users. The status log of an IM user is a list of pairs of the form (time, state), where state is an element of a small set, such as {online, offline, busy, away}, and time is the time at which the member switched into that state. Resig et. al. show [12] that, in spite of their simplicity, status logs contain a great deal of structure. Since any pair of IM users can instant message each other only if they are both online at the same time, it seems reasonable to guess that any two IM users that are frequently online at the same time may in fact be frequently instant messaging each other. This hypothesis forms the basis of each of our association measures. For a chosen population of IM users, we compared the social networks obtained using our relationship measures to the social network formed in LiveJournal (www.livejournal.com) by the population. LiveJournal is a blogging community that allows users to explicitly name other LiveJournal users as associates. The network obtained by these association lists thus acts as a control of sorts for validating our IM-based association measure.
Record URI: http://hdl.handle.net/1850/9166
Date: 2004

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