Constructing a Chinese Conversation Corpus for Sentiment Analysis

Yujun Zhou, Changliang Li, Bo Xu, Jiaming Xu, Lei Yang, Bo Xu

Abstract: Sentiment analysis plays an important role in many applications. This paper introduces our ongoing work related to the sentiment analysis on Chinese conversation. The main purpose is to construct a Chinese conversation corpus for sentiment analysis and provide a benchmark result on this corpus. To explore the effectiveness of machine learning based approaches for sentiment analysis on Chinese conversation, we firstly collected conversational data from some online English learning websites and our instant messages, and manually annotated it with three sentiment polarities and 22 fine-grained emotion classes. Then we applied multiple representative classification methods to evaluate the corpus. The evaluation results provide good suggestions for the future research. And we will release the corpus with gold standards publicly for research purposes.

External IDs:dblp:conf/nlpcc/ZhouLXXYX17