Topic opinion leader identification based on latent Dirichlet allocation topic model

Ying Zhao; Huili Deng; Tian Qiang

doi:10.1117/12.3004095

11 October 2023 Topic opinion leader identification based on latent Dirichlet allocation topic model

Ying Zhao, Huili Deng, Tian Qiang

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 1280047 (2023) https://doi.org/10.1117/12.3004095
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

This paper focuses on the indicator of professional authority for mining user proficiency within a specific topic domain, which contributes to Sina Weibo opinion leader identification. We construct an indicator system based on three dimensions comprising user attributes, interaction behaviors, and topic extraction. We quantify the professional authority indicator by applying the latent Dirichlet allocation topic model and information entropy. The grey relational analysis and the entropy-weight method are employed to calculate the opinion leader index and rank candidates accordingly, reflecting influence within a topic domain. And we validate the proposed method by analyzing a typical event of "Wei Ya's tax evasion" as an experimental case. Results demonstrate that the proposed model effectively identifies highly influential users with proficiency in this topic, these opinion leaders could play a guiding role in information diffusion. Moreover, it can serve as a reference for selecting opinion leaders in similar topic events as a prediction method. This paper supports regulatory agencies and Sina Weibo regarding online public opinion control, guidance, and response.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ying Zhao, Huili Deng, and Tian Qiang "Topic opinion leader identification based on latent Dirichlet allocation topic model", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 1280047 (11 October 2023); https://doi.org/10.1117/12.3004095

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KEYWORDS

Data modeling

Visualization

Web 2.0 technologies

Analytical research

Mining

Reflection

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