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Emotional reactions to real-world events in social networks

Nguyen, Thin, Phung, Dinh, Adams, Brett and Venkatesh, Svetha 2011, Emotional reactions to real-world events in social networks, in New Frontiers in Applied Data Mining : Proceedings of the PAKDD 2011 International Workshops, Springer, Heidelberg, Germany, pp. 53-64, doi: 10.1007/978-3-642-28320-8_5.

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Title Emotional reactions to real-world events in social networks
Author(s) Nguyen, ThinORCID iD for Nguyen, Thin orcid.org/0000-0003-3467-8963
Phung, DinhORCID iD for Phung, Dinh orcid.org/0000-0002-9977-8247
Adams, Brett
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Conference name Pacific-Asia Conference on Knowledge Discovery and Data Mining (15th : 2011 : Shenzhen, China)
Conference location Shenzhen, China
Conference dates 24-27 May 2011
Title of proceedings New Frontiers in Applied Data Mining : Proceedings of the PAKDD 2011 International Workshops
Editor(s) [Unknown]
Publication date 2011
Conference series Pacific-Asia Conference on Knowledge Discovery and Data Mining
Start page 53
End page 64
Total pages 12
Publisher Springer
Place of publication Heidelberg, Germany
Keyword(s) emotional reaction
sentiment index
sentiment burst
bursty event
Summary 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.
ISBN 9783642283192
ISSN 0302-9743
Language eng
DOI 10.1007/978-3-642-28320-8_5
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2012, Springer-Verlag Berlin Heidelberg
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044917

Document type: Conference Paper
Collection: Centre for Pattern Recognition and Data Analytics
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