Optimization And Implementation Of The Network Public Opinion Information Monitoring System In Colleges And Universities

With the rapid development of network informatization,there are more and more public opinion information on the network.At present,network public opinion is a hot topic.With the continuous popularization and use of the network,information technology has been deeply rooted in the hearts of the people,and the dissemination of information is more and more convenient and faster.Some topics are discussed all the time in the network,However,some sensitive topics need to be monitored and controlled.People also like to vent some bad things or negative materials through anonymous network,and then decorate them to attract people's attention and gain traffic,so as to mislead the public's value orientation.There are both good and bad topics on the Internet.If they are not controlled,they will have a serious impact.Their spread is very wide and fast,and they are spread in a way of brainwashing.They are also a microcosm of society.Online social communication even occupies a larger position among young people than real social communication.As a combination of social science and natural science,it is studied as an important issue in both computer science and social science.In this paper,the design of the network public opinion information monitoring system is understood through the literature reference method,and then through the opinion collection of the departments in charge of public opinion management in Colleges and universities,the common points and differences are unified,and the public opinion monitoring system is optimized to make it more suitable for the use of colleges and universities.Based on the above,this paper proposes a distributed information collection method to collect the data of university websites and major social platforms,and then uses convolution neural network(CNN)algorithm to classify the collected data of network public opinion information,so as to judge the positive and negative emotions of college students,which can more effectively guide the values and ideological and political education of college students,Finally,hot topic tracking and intelligent monitoring.The final system is feasible after testing.