Predicting subjectivity orientation of online forum threads

Authors:
Prakhar Biyani;Cornelia Caragea;Prasenjit Mitra
Affiliations:
The Pennsylvania State University;University of North Texas;The Pennsylvania State University
Venue:
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 2
Year:
2013

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Abstract

Online forums contain huge amounts of valuable information in the form of discussions between forum users. The topics of discussions can be subjective seeking opinions of other users on some issue or non-subjective seeking factual answer to specific questions. Internet users search these forums for different types of information such as opinions, evaluations, speculations, facts, etc. Hence, knowing subjectivity orientation of forum threads would improve information search in online forums. In this paper, we study methods to analyze subjectivity of online forum threads. We build binary classifiers on textual features extracted from thread content to classify threads as subjective or non-subjective. We demonstrate the effectiveness of our methods on two popular online forums.