Sentiment analysis of microblog combining dictionary and rules
Ding Yuan, Yanquan Zhou, Ruifan Li, Peng Lu · 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) · 2014
Microblog has become a daily communication tool in recent years. Researches on microblog have drawn more and more attention. Microblogging emotional classification is a major research of user intent analysis based on User-Generated Content (UGC). This paper focuses on the discrimination on two emotional tendencies: positive and negative. Firstly, the system cleared the noisy elements in the microblog, then extracted the features of the microblog and finally classified the microblog using Support Vector Machine (SVM). Furthermore, we improve the algorithms of feature extraction and weight computing combining dictionary approach and rule based approach. The result of experiment shows that the method is effective.