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Emotional reactions to real-world events in social networks

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2012
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Conference Paper

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Nguyen, T. and Phung, D. and Adams, B. and Venkatesh, S. 2012. Emotional reactions to real-world events in social networks, in Cao, L. and Huang, J.Z. and Bailey, J. and Koh, Y.S. and Luo, J. (ed), 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), May 24-27 2011, pp. 53-64. Shenzhen, China: Springer-Verlag.
Source Title
Lecture Notes in Artificial Intelligence 7104. New Frontiers in Applied Data Mining
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15th Pacific-Asia Conference on Knowledge Discovery and Data Mining
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Department of Computing
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Abstract

A convergence of emotions among people in social networks is potentially resulted by the occurrence of an unprecedented event in real world. E.g., a majority of bloggers would react angrily at the September 11 terrorist attacks. Based on this observation, we introduce a sentiment index, computed from the current mood tags in a collection of blog posts utilizing an affective lexicon, potentially revealing subtle events discussed in the blogosphere. We then develop a method for extracting events based on this index and its distribution. Our second contribution is establishment of a new bursty structure in text streams termed a sentiment burst. We employ a stochastic model to detect bursty periods of moods and the events associated. Our results on a dataset of more than 12 million mood-tagged blog posts over a 4-year period have shown that our sentiment-based bursty events are indeed meaningful, in several ways.