Abstract: As the current mainstream Internet social media, Weibo allows its users to post information about events involved with the “River Chief System” anytime and anywhere on it. Extracting and classifying events improves the efficiency of discovering and solving problematic events in the management of river chief system, and also helps monitor and analyze the evaluation of the management status of river and lake shorelines for the people. The “Internet +” technology has been playing a tremendous role in the management of river chief system. In the present paper, the application of Weibo’s big data in the management of river chief system is discussed at first. A framework of text information mining system for Weibo is proposed based on the large amount of text description contained in social media. News and public information about events involved with river chief system can be captured by using Internet crawling technology and semantic recognition analysis technology via this framework. Tags of the events such as time, location, and type are identified and extracted, and finally people’s emotional tendencies are analyzed through data mining. With the data of Pearl River network from June 2018 to December 2020 on Weibo as a case study, the correctness of the model in training set reaches 88.6%, implying the feasibility of the model. The public opinion analysis system can help improve the management efficiency of the river chief system.

Key words: Internet big data, text processing, River Chief System Management, public opinion analysis, semantic modeling