Research On Topic Oriented Sentiment Analysis Based On Ontology

In allusion to the unlighted public opinion information, the important aspects of public opinion analysis are as follows: network hot spots, focus and sensitive topic mining, public opinion trends control, the ability to handle and monitor the network emergency improvement and so on. Topic sentiment analysis is an important part of public opinion analysis. In order to judge the tendency of the emotional words and the overall orientation of the topics, sentiment analysis of the specific network resources is done in this paper.The purpose of this paper is to analysis the sentiment of some network topic. Firstly, the domain ontology of some specific topic is constructed based on semi-automatic ontology learning methods, based on which we can filter out the corpus of the topic we want from the corpus of multiple topics. Then, in order to get the overall tendency of the topic, the knowledge of fine-grained classification and the intensity value of the vocabulary in the sentiment vocabulary ontology is used to analysis the sentiment of the corpus that have already been filtered out. Finally, an application example of topic oriented sentiment analysis is introduced, and the main function modules of the Spring Festival Evening evaluation system are completed. The main work of this paper is as follows.(1) Ontology construction. This section includes two parts, one is the construction of domain ontology about a specific network topic, and another is the sentiment vocabulary ontology construction. The former is used to filter out certain topics from the basic corpus with multiple topics. The latter is designed to guide the fine-grained classification of the emotional corpus.(2) Topic Corpus Construction. First, the Web corpus is crawled automatically, the texts of the corpus are clustered after being pre-processed in order to build multi-topic corpus, and then the topic corpus is build based on the domain ontology in order to form a single topic corpus.(3) Topic oriented sentiment analysis. The key task of the topic oriented sentiment analysis is the extraction and calculation of subjective information, including subjective sentences text extraction from the corpus, subjective emotional words extraction from a sentence, and ontology-based emotional words'tendency calculation. Finally, experiments show that the sentiment analysis algorithm is effective. (4) Application. This paper presents an application example of topic oriented sentiment analysis. The main function modules of the Spring Festival Evening evaluation system are described in detail. This system shows that topic oriented sentiment analysis is suitable to applied to network monitoring system of public opinion.