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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Seo, J., Croft, W., Smith, D.: Online community search using thread structure. In: CIKM, pp. 1907–1910. ACM (2009)
Bhatia, S., Mitra, P.: Adopting inference networks for online thread retrieval. In: Proceedings of the 24th AAAI, pp. 1300–1305 (2010)
Hu, M., Liu, B.: Mining and summarizing customer reviews. In: SIGKDD, pp. 168–177. ACM (2004)
Liu, B.: Sentiment analysis and subjectivity. In: Handbook of Natural Language Processing (2010) ISBN: 978–1420085921
Ly, D., Sugiyama, K., Lin, Z., Kan, M.: Product review summarization from a deeper perspective. In: JCDL, pp. 311–314 (2011)
Li, B., Liu, Y., Ram, A., Garcia, E., Agichtein, E.: Exploring question subjectivity prediction in community qa. In: SIGIR, pp. 735–736. ACM (2008)
Gurevych, I., Bernhard, D., Ignatova, K., Toprak, C.: Educational question answering based on social media content. In: Proceedings of the 14th International Conference on Artificial Intelligence in Education. Building Learning Systems that Care: From Knowledge Representation to Affective Modelling, pp. 133–140 (2009)
Stoyanov, V., Cardie, C., Wiebe, J.: Multi-perspective question answering using the opqa corpus. In: EMNLP, pp. 923–930. Association for Computational Linguistics (2005)
Yu, H., Hatzivassiloglou, V.: Towards answering opinion questions: Separating facts from opinions and identifying the polarity of opinion sentences. In: EMNLP, pp. 129–136. Association for Computational Linguistics (2003)
Pang, B., Lee, L.: Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval 2, 1–135 (2008)
Somasundaran, S., Wilson, T., Wiebe, J., Stoyanov, V.: Qa with attitude: Exploiting opinion type analysis for improving question answering in on-line discussions and the news. In: ICWSM (2007)
Seki, Y., Eguchi, K., Kando, N., Aono, M.: Multi-document summarization with subjectivity analysis at duc 2005. In: DUC. Citeseer (2005)
Carenini, G., Ng, R., Pauls, A.: Multi-document summarization of evaluative text. In: EACL, pp. 305–312 (2006)
Biyani, P., Bhatia, S., Caragea, C., Mitra, P.: Thread specific features are helpful for identifying subjectivity orientation of online forum threads. In: COLING, pp. 295–310. ACL, Mumbai (2012)
Bruce, R., Wiebe, J.: Recognizing subjectivity: a case study in manual tagging. Natural Language Engineering 5, 187–205 (1999)
Riloff, E., Wiebe, J.: Learning extraction patterns for subjective expressions. In: EMNLP, pp. 105–112. ACL (2003)
Li, B., Liu, Y., Agichtein, E.: Cocqa: co-training over questions and answers with an application to predicting question subjectivity orientation. In: EMNLP, pp. 937–946. ACL, Stroudsburg (2008)
Yu, H., Hatzivassiloglou, V.: Towards answering opinion questions: separating facts from opinions and identifying the polarity of opinion sentences. In: EMNLP, pp. 129–136. ACL, Stroudsburg (2003)
Aikawa, N., Sakai, T., Yamana, H.: Community qa question classification: Is the asker looking for subjective answers or not? IPSJ Online Transactions 4, 160–168 (2011)
Mitchell, T.: Machine learning. McGraw-Hill, Burr Ridge (1997)
Dietterich, T.G.: Ensemble methods in machine learning. In: Kittler, J., Roli, F. (eds.) MCS 2000. LNCS, vol. 1857, pp. 1–15. Springer, Heidelberg (2000)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.: The weka data mining software: an update. ACM SIGKDD Explorations Newsletter 11, 10–18 (2009)
Yang, Y., Pedersen, J.: Feature selection in statistical learning of text categorization. In: Proc. ICML, pp. 412–420 (1997)
Kubat, M., Matwin, S.: Addressing the curse of imbalanced training sets: One-sided selection. In: ICML, pp. 179–186. Morgan Kaufmann (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Biyani, P., Caragea, C., Mitra, P. (2013). Predicting Subjectivity Orientation of Online Forum Threads. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2013. Lecture Notes in Computer Science, vol 7817. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37256-8_10
Download citation
DOI: https://doi.org/10.1007/978-3-642-37256-8_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37255-1
Online ISBN: 978-3-642-37256-8
eBook Packages: Computer ScienceComputer Science (R0)