Collective classification of user emotions in twitter

İleri, İbrahim
The recent explosion of social networks has generated a big amount of data including user opinions about varied subjects. For classifying the sentiment of user postings, many text-based techniques have been proposed in the literature. As a continuation of sentiment analysis, there are also studies on the emotion analysis. Because of the fact that many different emotions are needed to be dealt with at this point, the problem becomes much more complicated. In this thesis, a different user-centric approach is considered that connected users may be more likely to hold similar emotions; therefore, leveraging relationship information can complement user-level sentiment inference task in social networks. Employing Twitter as a source for experimental data and working with a proposed collective classification algorithm, users whose emotions are not known on subject, are predicted in an effective and collaborative setting.


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Citation Formats
İ. İleri, “Collective classification of user emotions in twitter,” M.S. - Master of Science, Middle East Technical University, 2015.