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Research on the Visualization Method of Weibo User Sentiment Analysis Based on IP Affiliation and Comment Content

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Spatial Data and Intelligence (SpatialDI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13887))

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Abstract

Aiming at the problems of huge number of comments in Weibo, complex data format, inconsistent emotion model, vague emotion identification and lack of effective spatial location expression, a visual research method of emotion analysis of Weibo users based on IP affiliation and comment content is proposed in combination with the open IP affiliation function of Weibo in 2022. The proposed method uses crawler to obtain Weibo comment data, and uses manual tagging and machine learning methods to segment words and analyze emotions of comment content; Finally, two methods are proposed to form maps by combining spatio-temporal data such as time and coordinates. Experimental results show that this method is feasible and effective for the visualization of emotion analysis of Weibo users, and can achieve better visualization results.

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Correspondence to Xiang Li .

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Geng, H., Li, X., Liu, W., Zhao, W., Ren, F. (2023). Research on the Visualization Method of Weibo User Sentiment Analysis Based on IP Affiliation and Comment Content. In: Meng, X., et al. Spatial Data and Intelligence. SpatialDI 2023. Lecture Notes in Computer Science, vol 13887. Springer, Cham. https://doi.org/10.1007/978-3-031-32910-4_5

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  • DOI: https://doi.org/10.1007/978-3-031-32910-4_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-32909-8

  • Online ISBN: 978-3-031-32910-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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