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Analysis of viewpoint evolution based on WeiBo data mining.

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Bibliographic Details
Title: Analysis of viewpoint evolution based on WeiBo data mining.
Authors: Tang, Sichen1 (AUTHOR), Fang, Aili1 (AUTHOR) fangaili@hotmail.com
Source: Applied Mathematics & Computation. Apr2025, Vol. 491, pN.PAG-N.PAG. 1p.
Subjects: Data mining, Sentiment analysis, Public opinion, Public communication, Artificial intelligence
Abstract: In the era of rapid development of the Internet, in order to reflect the evolution process of users' viewpoints on network relations, a Bayesian viewpoint evolution model based on Weibo data mining is proposed by studying the relationship between the viewpoints of the author and those of the forwarders on the Sina Weibo platform. Firstly, Python crawler technology was used to crawl the comments and forwarding data under the Weibo topic "#ChatGPT father says human-level AI is coming soon". After data preprocessing and sentiment analysis, the user relationship network diagram was drawn with Gephi software. Secondly, the viewpoint evolution model is constructed and the viewpoint update formula based on Bayes rule is used to calculate the users' viewpoint evolution within the network relations of several kinds of different publication centers. The results show that: in the communication of public opinion, the evolution direction of the opinions of the media-centered network relations tends to be more consistent, which indicates the importance of the opinion guidance of the media in the communication of information. The analysis and technology provide a certain reference for the government and the media to control and guide the network public opinion. • Explore user network relationships based on crowd portraits and emotional analysis. • Constructed a viewpoint updating model based on Bayes rule. • Viewpoint evolution modeling combined with empirical analysis. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:In the era of rapid development of the Internet, in order to reflect the evolution process of users' viewpoints on network relations, a Bayesian viewpoint evolution model based on Weibo data mining is proposed by studying the relationship between the viewpoints of the author and those of the forwarders on the Sina Weibo platform. Firstly, Python crawler technology was used to crawl the comments and forwarding data under the Weibo topic "#ChatGPT father says human-level AI is coming soon". After data preprocessing and sentiment analysis, the user relationship network diagram was drawn with Gephi software. Secondly, the viewpoint evolution model is constructed and the viewpoint update formula based on Bayes rule is used to calculate the users' viewpoint evolution within the network relations of several kinds of different publication centers. The results show that: in the communication of public opinion, the evolution direction of the opinions of the media-centered network relations tends to be more consistent, which indicates the importance of the opinion guidance of the media in the communication of information. The analysis and technology provide a certain reference for the government and the media to control and guide the network public opinion. • Explore user network relationships based on crowd portraits and emotional analysis. • Constructed a viewpoint updating model based on Bayes rule. • Viewpoint evolution modeling combined with empirical analysis. [ABSTRACT FROM AUTHOR]
ISSN:00963003
DOI:10.1016/j.amc.2024.129212