User-Level Opinion Propagation Analysis in Discussion Forum Threads

Online discussions such as forums are very popular and enable participants to read other users’ previous interventions and also to express their own opinions on various subjects of interest. In online discussion forums, there is often a mixture of positive and negative opinions because users may have similar or conflicting opinions on the same subject. Therefore, it is challenging to track the flow of opinions over time in online discussion forums. Past research in the field of opinion propagation has dealt mainly with online social networks. In this paper, by contrast, we address the opinion propagation in discussion forum threads. We proposed a user-level opinion propagation analysis method in the discussion forum threads. This method establishes for a given time step whether the discussion will result in complete agreement between participants or in disparate and even contrary opinions.

[1]  Deborah Richards,et al.  Knowledge Management and Acquisition for Smart Systems and Services , 2014, Lecture Notes in Computer Science.

[2]  Marilyn A. Walker,et al.  A Corpus for Research on Deliberation and Debate , 2012, LREC.

[3]  Krishna P. Gummadi,et al.  Measurement and analysis of online social networks , 2007, IMC '07.

[4]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[5]  Anna Stavrianou.  Modeling and mining of Web discussions , 2010 .

[6]  Masahiro Kimura,et al.  Finding Relation between PageRank and Voter Model , 2010, PKAW.

[7]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[8]  Reza Zafarani,et al.  Sentiment Propagation in Social Networks: A Case Study in LiveJournal , 2010, SBP.

[9]  Katarzyna Sznajd-Weron,et al.  Opinion evolution in closed community , 2000, cond-mat/0101130.

[10]  Luciano da F. Costa,et al.  SURVIVING OPINIONS IN SZNAJD MODELS ON COMPLEX NETWORKS , 2005 .

[11]  Bing Liu,et al.  Mining and summarizing customer reviews , 2004, KDD.

[12]  Rainer Hegselmann,et al.  Opinion dynamics and bounded confidence: models, analysis and simulation , 2002, J. Artif. Soc. Soc. Simul..

[13]  John Yen,et al.  Advances in Web Mining and Web Usage Analysis, 8th International Workshop on Knowledge Discovery on the Web, WebKDD 2006, Philadelphia, PA, USA, August 20, 2006, Revised Papers , 2007, WebKDD.

[14]  Janyce Wiebe,et al.  Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis , 2005, HLT.

[15]  Timothy W. Finin,et al.  Why We Twitter: An Analysis of a Microblogging Community , 2009, WebKDD/SNA-KDD.

[16]  Andrea Esuli,et al.  SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining , 2010, LREC.

[17]  Pattarachai Lalitrojwong,et al.  Mining Feature-Opinion in Online Customer Reviews for Opinion Summarization , 2010, J. Univers. Comput. Sci..

[18]  Patricia L. Mabry,et al.  Advances in Social Computing, Third International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010, Bethesda, MD, USA, March 30-31, 2010. Proceedings , 2010, SBP.

[19]  Soo-Min Kim,et al.  Determining the Sentiment of Opinions , 2004, COLING.

[20]  Hinrich Schütze,et al.  Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.

[21]  Martha Palmer,et al.  Verb Semantics and Lexical Selection , 1994, ACL.

[22]  Raymond J. Mooney,et al.  Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing , 2005 .

[23]  Stefan Trausan-Matu,et al.  Opinion Propagation in Online Social Networks: A Survey , 2014, WIMS '14.

[24]  Guillaume Deffuant,et al.  Mixing beliefs among interacting agents , 2000, Adv. Complex Syst..