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Title:Tweeting Questions in Academic Conferences: Seeking or Promoting Information?
Author(s):Wen, Xidao; Lin, Yu-Ru
Subject(s):information seeking/retrieval
social media
text/data/knowledge mining
Abstract:The fast growth of social media has reshaped the traditional way of human interaction and information seeking behavior, which draws research attention on characterizing the new information seeking paradigm. However, results from previous studies might not be well grounded under certain social settings. In this paper, we leverage machine learning techniques to identify different types of question tweets within academic communities as an example of one particular social context. By studying over 160 thousands of tweets posted by 30 academic communities, we discovered a different landscape of information-seeking behaviors, where less tweets are regarded as question tweets, and more real information-seeking tweets are observed. We also found that users respond differently with different types of question tweets. We believe our study would be beneficial for understanding the information seeking behaviors in social media.
Issue Date:2015-03-15
Series/Report:iConference 2015 Proceedings
Genre:Conference Poster
Peer Reviewed:yes
Rights Information:Copyright 2015 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.
Date Available in IDEALS:2015-03-24

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