Sentiment Analysis of Social Issues

Sentiment analysis refers to a broad range of fields of natural language processing, computational linguistics, and text mining. Sentiment classification of reviews and comments has emerged as the most useful application in the area of sentiment analysis. Bag of words and feature based sentiment are the most popular approaches used by researchers to deal with sentiment analysis of opinions about products such as movies, electronics, cars etc. Up until recently most researches have been done on the sentiment analysis of products and services. This paper focuses on the sentiment analysis of social issues. In this paper we initially conduct a statistical investigation on the differences between sentiment analysis of products and social issues. Then, based on our findings, we propose an approach to take into account the role of verb as the most important term in expressing opinions regarding the social issues. Statistical and experimental results show that considering verbs not only is required and undeniable, but also improves the performance of sentiment analysis.