Detecting chronic critics based on sentiment polarity and user’s behavior in social media

Abstract

There are some chronic critics who always 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 comments are informal, and, there are sarcastic and incomplete contexts. This means that it is difficult for current NLP technology 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 experimental results show that the proposed method outperforms analysis based only on opinion mining techniques.