2012 | OriginalPaper | Chapter
Emotional Reactions to Real-World Events in Social Networks
Authors : Thin Nguyen, Dinh Phung, Brett Adams, Svetha Venkatesh
Published in: New Frontiers in Applied Data Mining
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
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.