Paper: Detecting Chronic Critics Based on Sentiment Polarity and User’s Behavior in Social Media

ACL ID P13-3016
Title Detecting Chronic Critics Based on Sentiment Polarity and User’s Behavior in Social Media
Venue Annual Meeting of the Association of Computational Linguistics
Session Student Session
Year 2013
Authors

There are some chronic critics who al- ways complain about the entity in social media. We are working to automatically detect these chronic critics to prevent the spread of bad rumors about the reputation of the entity. In social media, most com- ments are informal, and, there are sarcas- tic and incomplete contexts. This means that it is difficult for current NLP technol- ogy such as opinion mining to recognize the complaints. As an alternative approach for social media, we can assume that users who share the same opinions will link to each other. Thus, we propose a method that combines opinion mining with graph analysis for the connections between users to identify the chronic critics. Our ex- perimental results show that the proposed method outperforms analysis based only on opinion min...