A Study on Sentiment Computing and Classification of Sina Weibo with Word2vec

In recent years, Weibo has greatly enriched people´s life. More and more people are actively sharing information with others and expressing their opinions and feelings on Weibo. Analyzing emotion hidden in this information can benefit online marketing, branding, customer relationship management and monitoring public opinions. Sentiment analysis is to identify the emotional tendencies of the microblog messages, that is to classify users´ emotions into positive, negative and neutral. This paper presents a novel model to build a Sentiment Dictionary using Word2vec tool based on our Semantic Orientation Pointwise Similarity Distance (SO-SD) model. Then we use the Emotional Dictionary to obtain the emotional tendencies of Weibo messages. Through the experiment, we validate the effectiveness of our method, by which we have performed a preliminary exploration of the sentiment analysis of Chinese Weibo in this paper.