Challenges of Sentiment Analysis for Dynamic Events

Abstract

Efforts to assess people’s sentiments on Twitter have suggested that Twitter could be a valuable resource for studying political sentiment and that it reflects the offline political landscape. Many opinion mining systems and tools provide users with people’s attitudes toward products, people, or topics and their attributes/aspects. However, although it may appear simple, using sentiment analysis to predict election results is difficult, since it is empirically challenging to train a successful model to conduct sentiment analysis on tweet streams for a dynamic event such as an election. This article highlights some of the challenges related to sentiment analysis encountered during monitoring of the presidential election using Kno.e.sis’s Twitris system.

DOI: 10.1109/MIS.2017.3711649

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Cite this paper

@article{Ebrahimi2017ChallengesOS, title={Challenges of Sentiment Analysis for Dynamic Events}, author={Monireh Ebrahimi and Amir Hossein Yazdavar and Amit P. Sheth}, journal={IEEE Intelligent Systems}, year={2017}, volume={32}, pages={70-75} }