The Research On Network Public Opinion Acquisition And Analysis Algorithm

With the rapid development of Internet technology,network media has become the main way for people to obtain information,and the network public opinion has emerged.Internet public opinion is popular on the internet on the social events of different network opinion,the public can speak freely,exercise their own supervision,the right to know,the right to express and participate in the right to a certain extent,which affected the country's network security.Therefore,it is necessary to monitor and supervise the network public opinion,to prevent the social harm of misleading speech and to create a positive social atmosphere.In order to carry out network public opinion analysis,need to automatically obtain a large number of public opinion data from the news page,after the hotspot extraction algorithm is divided into different topics cluster,and when necessary to re-establish a new topic cluster.Through the network public opinion changes cycle to grasp the development of public opinion over time,the Chinese word segmentation of each news of the key words,the collection of pages for K-means clustering analysis to get hot,you can get an event from the emergence of the dormant process of migration The This can help people quickly find valuable information to help monitor and real-time understanding of the overall network of public opinion,this paper analyzes the use of K-Means algorithm to meet the above needs.The government can grasp the latest public opinion through the network public opinion hot spot,guide the public to correctly view the problem and create an active and healthy social atmosphere.At the same time,the public can establish the correct values in the subtle influence and help the construction of democracy and the rule of law and spiritual civilization.