Identifying Word Sentiment Orientation for Free Comments via Complex Network
利用复杂网络为自由评论鉴定词汇情感倾向性

Identifying word sentiment orientation (WSO) is usually the foundation of mining coarse-grained emotion information. In free comments, there exist many grammatical errors which disable previous grammatical text-based methods in identifying WSO for free comments, and there exist some context-sensitive words which disable offline opinion words in mining coarse-grained emotion information. In view of the above questions, a new method which identifies WSO for free comments via complex network is proposed. This method consists of two parts. The first part makes use of context information in free comments to build a sentiment orientation relationship network (SORN) for effectively solving the context sensitive and noise problems. For this purpose, two algorithms are brought forward. One is the algorithm for building the pyramid anti-noise information model and the other is the algorithm for optimizing the sentiment orientation relationship network by anti-noise information. The second part identifies WSO for free comments via SORN. For this purpose, the SORN-based WSO algorithm is put forward. Experimental results show that our method far exceeds HM in identifying WSO for free comments and has good timeliness.