Network public sentiment orientation analysis based on HMM Model

In recent years, the web has become one of the main carrier of social public opinion, so the network public opinion needed a new natural language processing technology to identify the information efficiently and accurately, analysis and classify the public opinions effectively. In this paper, the text semantic orientation analysis method is proposed based on Hidden Markov Model to improve the accuracy of the network public opinion orientation analysis. Reference the thought of emotional vocabulary tendency analysis method, and consider the context to analysis the semantic orientation of the text. Experimental results show that, this algorithm can improve the stability and accuracy of network public opinion orientation analysis effectively.