Research On Topic Detection And Sentiment Analysis Based Ontology Of Chinese Microblog

The brief writing, convenient releaseing and real-time interaction features of Microblogging attractmore and more people to update messages, exchange ideas on the microblogging. Consequently,microblogging platform developed rapidly, and it provides increasing rich applications. Hugemicroblogging messages seem disorganized, no rules, but in fact there are a number of topics among thesemessages. How to identify hot topics from the massive microblogging messages, and analyze theorientation of hot topics becomes a new application.The purpose of this paper is to analyze the topic detection and sentiment of topic in micoblogging.First analyze the latest domestic and international methods of topic discovery and orientation analysis inmicroblogging. Second design a topic detection algorithm in micobloggings. Third compute the orientationof hot topic using emotional word ontology, rule sets and microblogging emoticons. Finally, design a hottopic detection and orientation analysis of topics prototype systems based on the datas released on the Sinamicroblogging platform during January15,2013to Febuary5,2013. The main work of this paper is asfollows:(1) Emotional words ontology construction. On the one hand, collecting and summarizeing the currentexisting emotional vocabulary resources to build a basic emotional word ontology, on the other hand,collecting Network emotion terms to increase the accuracy of topic orientation.(2) Microblogging topic detection. First merge the microblogging messages with the same theme togenerate a single microblogging tree, and form a long text document, which is indicated by3-Gram model;then merge the single microblogging trees that have high theme sililarity to form a document that has alatent topic. Finally, extrat the topic from the document, and calculate the heat of each topic.(3) Microblogging topic orientation analysis. Analyzing the context of the sentence semanticrelationships to establish the rule set based on linguistic knowledge. The subjective3-POS models areextracted based on the emotional vocabulary ontology, microblogging emoticons and rule set. Finally, thesentiment orientation of the3-POS models is calculated. As a result, the sentiment orientation of topic iscomputed.(4) Microblogging topic detection and orientation analysis application research. A hot topic detection and orientation analysis of topics prototype systems is designed based on the datas released on the Sinamicroblogging platform during January15,2013to Febuary5,2013. This system shows the practicalapplicability of the research in this paper.