Topic-Based Chinese Message Polarity Classification System at SIGHAN8-Task2

This paper describes the topic-based Chinese message polarity classification system submitted by LCYS_TEAM at SIGHAN8-Task2. The system mainly includes two parts: 1) a graph-based ranking model integrating local and global information is adopted to represent the classification ability of words towards different topics. In construction of graph model, a new weighting approach and a PMI-based random jumping probability selection method is proposed. 2) For sentimental features, word embedding is employed for acquiring expanded topical words and syntactic dependency is adopted for getting topic-related sentimental words. Experiment results demonstrate the effectiveness of our system.