Online debate summarization using topic directed sentiment analysis

  • Authors:

  • Sarvesh Ranade;Jayant Gupta;Vasudeva Varma;Radhika Mamidi

  • Affiliations:

  • International Institute of Information Technology, Hyderabad;International Institute of Information Technology, Hyderabad;International Institute of Information Technology, Hyderabad;International Institute of Information Technology, Hyderabad

  • Venue:
  • Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

Social networking sites provide users a virtual community interaction platform to share their thoughts, life experiences and opinions. Online debate forum is one such platform where people can take a stance and argue in support or opposition of debate topics. An important feature of such forums is that, they are dynamic and increase rapidly. In such situations, effective opinion summarization approaches are needed so that readers need not go through the entire debate. This paper aims to summarize online debates by extracting highly topic relevant and sentiment rich sentences. The proposed approach takes into account topic relevant, document relevant and sentiment based features to capture topic opinionated sentences. ROUGE scores are used to evaluate our system. Our system significantly outperforms several baseline systems and show 5.2% (ROUGE-1), 7.3% (ROUGE-2) and 5.5% (ROUGE-L) improvement over the state-of-the-art opinion summarization system. The results verify that topic directed sentiment features are most important to generate effective debate summaries.