The Research On The Emotion Tendency Of Network Public Opinion Hot Information

With the continuous development of Information Technology and Internet technology, make a large number of users published subjectivity remarks about inner perception, attitude, emotions and opinions in a more convenient and faster way for networks events, which form network public opinions. Network public opinions generally formed rapidly and in a short period of time have a huge impact on the society, therefore it is important to make a further study on network public opinions.The study of text emotion tendentiousness is not only a new and hot research direction in recent years, but also one of the important technologies researching on network public opinion. Text emotion tendentiousness classification study is a mining of a certain things, such as product, event, or the comment text to judge the emotional tendency of texts. Text emotional orientation analysis technology is widely used in many fields, in this article, will use the text emotional tendency analysis technique to analyze network public opinion information.On the Base of understanding the development situation on the research of network public opinions and text emotional tendency at home and abroad, author summarize the application situation and the analysis method of network public opinions and text emotional orientation analysis and puts forward own research content and the article structure. Furthermore, put the text emotional classification process as the main line, mainly research about Chinese word segmentation, stop words processing, feature selection and feature weighting calculating and text representation method, and emphatically introduces three kinds of text classification algorithm. Then author analyses the impact on classification results with different number of features and different number of positive and negative training data, gets a more suitable emotion analysis method to study network public opinion hot information through comparing the method of support vector machine (SVM), naive bayes(NB) and KNN and uses the text emotional tendency analysis technology to analyze network public opinion hot information. At the end of this paper, author choices the comments of hot issues "2012e-commerce price war" in the phoenix nets internet project as research object to makes a study of emotional tendencies classification and analyzes attitudes and opinions of users on this event at time moves. In addition, from the overall trend of the change of internet users emotional, analyzing the overall development situation of event, author exploring the reason about why positive and negative comments number are different, as well as to put forward his own views and opinions about the problems existing in the current e-commerce site.In this paper, the text emotional tendency analysis research on network public opinion hot information has certain theoretical significance and practical value. On one hand, this article through learning about network public opinion analysis and text emotional tendency analysis, put text emotional tendency technology into network public opinions and focuses on method of the text emotional tendency technology about network public opinion hot information in network environment, makes a detail research on application technology every link of the whole process in text emotional classification and realized the whole process from the corpus collection to text emotion classification, which not only enrich the research content of network public opinion and text sentiment analysis, but also has a certain supplementary role in promoting the theoretical development of related technology. On the other hand, using text emotional tendency analysis technology on network public opinion hot information analysis method combined with real examples, let social managers understand and analysis Community public opinion in a timely manner and judge events development situation and trend. It has certain practical significance to correct network early warning, guide the public opinion direction and maintain healthy and stable development of social economy.