Modeling Post-level Sentiment Evolution in Online Forum Threads

Dumitru-Clementin Cercel, Stefan Trausan-Matu

Abstract

Opinion propagation analysis in online forum threads is a relatively new research field emerging in the context of the increasing popularity of forums. Many changes occur over time in online forum threads since new users intervene in the discussion and express their opinions. In this paper, we propose a novel task in the analysis of opinion propagation in online forum threads, i.e. the modeling of post-level sentiment evolution in online forum threads. This task consists in the analysis of post-level sentiment evolution in an online forum thread in order to obtain a simplified model of this evolution. Based on opinion mining, graph theory, and post-level sentiment analysis, our method comprises five steps: removal of posts containing only facts, post-level sentiment identification, removal of posts with neutral sentiment, aggregation of parent-child vertices, and aggregation of sibling vertices. We evaluate the proposed method on real-world forum threads, and the results of our experiments are presented in the visualization interfaces.

References

  1. Baccianella, A. E. S. and Sebastiani, F. (2010). SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining. In Proceedings of the 7th conference on International Language Resources and Evaluation (LREC). European Language Resources Association (ELRA).
  2. Cercel, D.-C. and Trausan-Matu, S. (2014a). Opinion Influence Analysis in Discussion Forum Threads. In Proceeding of 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC). IEEE.
  3. Cercel, D.-C. and Trausan-Matu, S. (2014b). Opinion Propagation in Online Social Networks: A Survey. In Proceedings of the 4th International Conference on Web Intelligence, Mining and Semantics (WIMS). ACM.
  4. Cercel, D.-C. and Trausan-Matu, S. (2014c). User-Level Opinion Propagation Analysis in Discussion Forum Threads. In 16th International Conference on Artificial Intelligence: Methodology, Systems, Applications (AIMSA), pages 25-36, Springer International Publishing.
  5. Cormen, T. H., Leiserson, C. E., Rivest, R. L. and Stein, C. (2009). Introduction to Algorithms, Third Edition, The MIT Press.
  6. Ku, L.-W., Lee, L.-Y. and Chen, H.-H. (2006). Opinion extraction, summarization and tracking in news and blog corpora. Proceedings of AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs, pages 100-107.
  7. Manning, C. D. and Sch├╝tze, H. (1999). Foundations of statistical natural language processing, MIT Press.
  8. Walker, M. A., Tree, J. E. F., Anand, P., Abbott, R. and King, J. A. (2012). Corpus for Research on Deliberation and Debate. In Proceedings of the 8th conference on International Language Resources and Evaluation (LREC). European Language Resources Association (ELRA), pages 812-817.
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Paper Citation


in Harvard Style

Cercel D. and Trausan-Matu S. (2015). Modeling Post-level Sentiment Evolution in Online Forum Threads . In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-074-1, pages 588-593. DOI: 10.5220/0005286605880593


in Bibtex Style

@conference{icaart15,
author={Dumitru-Clementin Cercel and Stefan Trausan-Matu},
title={Modeling Post-level Sentiment Evolution in Online Forum Threads},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2015},
pages={588-593},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005286605880593},
isbn={978-989-758-074-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Modeling Post-level Sentiment Evolution in Online Forum Threads
SN - 978-989-758-074-1
AU - Cercel D.
AU - Trausan-Matu S.
PY - 2015
SP - 588
EP - 593
DO - 10.5220/0005286605880593