24 May 2012 Methods for extracting social network data from chatroom logs
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Abstract
Identifying social network (SN) links within computer-mediated communication platforms without explicit relations among users poses challenges to researchers. Our research aims to extract SN links in internet chat with multiple users engaging in synchronous overlapping conversations all displayed in a single stream. We approached this problem using three methods which build on previous research. Response-time analysis builds on temporal proximity of chat messages; word context usage builds on keywords analysis and direct addressing which infers links by identifying the intended message recipient from the screen name (nickname) referenced in the message [1]. Our analysis of word usage within the chat stream also provides contexts for the extracted SN links. To test the capability of our methods, we used publicly available data from Internet Relay Chat (IRC), a real-time computer-mediated communication (CMC) tool used by millions of people around the world. The extraction performances of individual methods and their hybrids were assessed relative to a ground truth (determined a priori via manual scoring).
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O. Isaac Osesina, O. Isaac Osesina, John P. McIntire, John P. McIntire, Paul R. Havig, Paul R. Havig, Eric E. Geiselman, Eric E. Geiselman, Cecilia Bartley, Cecilia Bartley, M. Eduard Tudoreanu, M. Eduard Tudoreanu, } "Methods for extracting social network data from chatroom logs", Proc. SPIE 8389, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR III, 83891H (24 May 2012); doi: 10.1117/12.920019; https://doi.org/10.1117/12.920019
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