Analysis And Research Of Network Public Opinion Based On Deep Learning In The 14th Five-Year Plan

The Five-Year Plan,or Five-Year Plan,is called The Nationality Law of The People's Republic of China,it is mainly to make plans for major national construction projects,the distribution of productive forces and the relationship of important proportions in the national economy,and to set goals and directions for the development of the national economy.In October 2020,the Fifth Plenary Session of the 19 th Central Committee of the Communist Party of China was held in Beijing,at which the 14 th five-year plan for National Economic and Social Development was formulated.The 14 th Five Year Plan for National Economic and Social Development and the outline of the long term goals for 2035 were reviewed and adopted by delegates at the 2021 and 2021,which were successfully convened from March 4to March 11.The completion of the 14 th Five Year Plan Not only outlines the general outline of economic development between 2021 and 2025,but also gives us a great deal of public opinion information,from which we can apply technical means to find hot topics and carry out public opinion statistics and analysis,discover the People's ideas and opinions on the National Development Plan under the new era development background,excavate the social conditions and public opinions,thus become an important reference to guide the next economic development direction.At present,there is no relevant research on the extraction of hot topics from the five-year plan outline and the use of technical means to carry out statistical analysis of public opinion on hot topics.In this paper,deep learning is used to complete the emotional analysis of the relevant text of the overall design.The main goal of sentiment analysis is to precisely locate the hot topics,quantify the public sentiment data of the 14 th five-year plan from various angles,and classify the positive sentiment and the negative sentiment of the text data.The main steps are:(1)Crawling initial data.Using Weibo as a platform,the data was culled from the text of comments by representative state media users who had published on the topic of the fifteen plan,such as “People's Daily,”“Global times,”“Xinhua news agency,”and other popular microbloggers,such as “Hu Xijin,”and “Sanmao on the sword of Meishan.”(2)Grasp the focus of public opinion.A clustering algorithm is used to classify the text,and a keyword extraction algorithm is designed to extract a set of keywords from each topic,which can accurately represent the content of the topic.(3)Refine the sentiment analysis model.Combined with the popular neural network model,the better analysis model is selected through comparative experiments,and the parameters are optimized to improve the analysis accuracy.(4)Designing methods of public opinion analysis.Scientific summary Planning public opinion data,get the final public opinion analysis results.