Simulation of Public Opinion Early Warning Model of Mobile Social Network Based on Big Data Algorithm

The spread of public opinion in mobile social networks needs the active guidance and control of the state. If public opinion cannot be effectively managed in a timely and accurate manner, it will inevitably have an adverse impact on the stability of the country and society. In this paper, the public opinion early warning model of mobile social network based on big data algorithm is proposed, which automatically crawls online comment data through web crawler, preprocesses it and stores it in the database. On the basis of constructing a social emotion dictionary, the automatic classification of social emotions is realized by combining various text classification algorithms, and the classification results are visualized. The simulation results show that the social sentiment analysis method of hot events based on text big data algorithm has achieved ideal experimental results, which proves the effectiveness of the social sentiment analysis model and method in this paper. With the development of public opinion, the trend of public opinion will continue to fluctuate. The media and the government should pay attention to the overall control of public opinion and take effective measures at the appropriate time to prevent the trend of public opinion from appearing huge ups and downs.