Building Corpus with Emoticons for Sentiment Analysis

Abstract

Corpus is an essential resource for data driven natural language processing systems, especially for sentiment analysis. In recent years, people increasingly use emoticons on social media to express their emotions, attitudes or preferences. We believe that emoticons are a non-negligible feature of sentiment analysis tasks. However, few existing works focused on sentiment analysis with emoticons. And there are few related corpora with emoticons. In this paper, we create a large scale Chinese Emoticon Sentiment Corpus of Movies (CESCM). Different to other corpora, there are a wide variety of emoticons in this corpus. In addition, we did some baseline sentiment analysis work on CESCM. Experimental results show that emoticons do play an important role in sentiment analysis. Our goal is to make the corpus widely available, and we believe that it will offer great support to sentiment analysis research and emoticon research.