Agricultural Network Public Opinion Monitoring System under Cloud Environment
With the rapid development of the Internet industry, people’s awareness of social practice participation has gradually increased. The way of public comment and expression of emotion has gradually changed from the original information media to the multimedia Internet platform. Accompanied by, various contradictions are easy to escalate and intensify. How to monitor the network public opinion in time and analyze it so as to take effective measures to deal with it is the key to solve social contradictions. Agricultural network public opinion also belongs to network public opinion. In view of the large amount of information related to agriculture generated by the network media such as news, forum, post bar, micro-blog, and the difficulty of public opinion monitoring, this paper puts forward the construction of agricultural net events in a timely manner and quickly take corresponding measures to pay attention to and guide the development of public opinion. Agriculture Internet Public Opinion (AIPO) is one of the important research directions of online public opinion. With the improvement of the quality of life, more Internet users have begun to pay attention to the “wood, oil and salt” and other agriculture-related grievances in daily life. How to do well in agricultural network is particularly important. work public opinion monitoring system under the cloud environment. The system uses the network crawler technology to capture the data related to agriculture, and uses the Principal Component Analysis method to reduce the dimension. In public opinion analysis, the nearest neighbor classification algorithm KNN is used to classify public opinion, and similarity rearrangement technology is used to filter duplicate information. The results show that the agricultural network public opinion monitoring system in the cloud environment proposed in this paper can detect the public opinion information and carry out scientific warning in time, which is of great significance in the agricultural field.