Public opinion evolution in social networks based on latent Dirichlet allocation and sentiment analysis

Xiao Li; Mengjie Ling; Chenyao Luo

doi:10.1117/12.3011657

7 December 2023 Public opinion evolution in social networks based on latent Dirichlet allocation and sentiment analysis

Xiao Li, Mengjie Ling, Chenyao Luo

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129412D (2023) https://doi.org/10.1117/12.3011657
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

In recent years, social network public opinion analysis technology, represented by text mining and sentiment analysis, has become an important tool to quickly understand public opinion. In this paper, we focus on the public opinion evolution in Sina Weibo and take the illustration event of textbooks in China’s primary schools in 2022 as an example. We crawl 13, 833 microblog hot comments on the illustration event of the textbook. Firstly, we pre-process the data, divide the evolution process into the outbreak period, the response period, and the final period, and give the word cloud and econometric analysis to display the data. Then, in order to study the public opinion evolution, we adopt the Latent Dirichlet Allocation (i.e., LDA) model and the lexicon-based sentiment analysis method. In particular, for each period, we capture the topic distribution of comments through the LDA model and learn the sentiment polarity through the lexicon-based sentiment analysis method. Finally, we utilize a knowledge graph to visualize results. The results show that during the outbreak period and response period, public sentiment is negative, and hot discussion topics are problems existing in the textbook, and also show their impact on education, and national ideology. In the final period, the discussion focuses on supporting the Ministry of Education to intervene in the strict inspection of elementary textbooks, and the public sentiment is positive.

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

Citation Download Citation

Xiao Li, Mengjie Ling, and Chenyao Luo "Public opinion evolution in social networks based on latent Dirichlet allocation and sentiment analysis", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129412D (7 December 2023); https://doi.org/10.1117/12.3011657

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KEYWORDS

Social networks

Mining

Machine learning

Analytical research

Visualization

Emotion

Intelligence systems

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