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Analysis of viewpoint evolution based on WeiBo data mining.

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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]
Copyright of Applied Mathematics & Computation is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
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  Data: Analysis of viewpoint evolution based on WeiBo data mining.
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  Data: <searchLink fieldCode="AR" term="%22Tang%2C+Sichen%22">Tang, Sichen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fang%2C+Aili%22">Fang, Aili</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> fangaili@hotmail.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Applied+Mathematics+%26+Computation%22">Applied Mathematics & Computation</searchLink>. Apr2025, Vol. 491, pN.PAG-N.PAG. 1p.
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  Data: <searchLink fieldCode="DE" term="%22Data+mining%22">Data mining</searchLink><br /><searchLink fieldCode="DE" term="%22Sentiment+analysis%22">Sentiment analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Public+opinion%22">Public opinion</searchLink><br /><searchLink fieldCode="DE" term="%22Public+communication%22">Public communication</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Applied Mathematics & Computation is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1016/j.amc.2024.129212
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      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Data mining
        Type: general
      – SubjectFull: Sentiment analysis
        Type: general
      – SubjectFull: Public opinion
        Type: general
      – SubjectFull: Public communication
        Type: general
      – SubjectFull: Artificial intelligence
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      – TitleFull: Analysis of viewpoint evolution based on WeiBo data mining.
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              Text: Apr2025
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              Y: 2025
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