Author(s)

Kuanwei Huang ¹, Weicong Mo ¹

Affiliation(s)

¹ Business School, Lingnan Normal University, Zhanjiang, China

Corresponding Author

Kuanwei Huang

ABSTRACT

This paper studies the topic of " Tokyo 2020(summer) Olympics " in Sina Weibo as the research target for topic mining by using latent dirichlet allocation (LDA) model and applying the sequence association rules algorithm to obtain the keywords among the different topic categories. Then we conduct the text content with sentiment analysis. Among the topics of the Tokyo Olympics, more than 74% of netizens have positive comments on the association rules under the keyword "gold medal", which parses out the competition sports that attract public attention, such as swimming, table tennis, shooting and other competitions that are well received and that will make the netizens pay more attention within. Finally, this study expects that it would continue to discover the sports hotspots for relevant departments with reference and assist the direction for the development of sports in China.

KEYWORDS

Tokyo Olympics; topic mining; sentiment analysis; sequence association rules

CITE THIS PAPER

Kuanwei Huang, Weicong Mo, The Topic Mining for Sentiment Analysis of Tokyo Olympic Games by Using LDA and Sequence Association Rules. Media and Communication Research (2024) Vol. 5: 44-51. DOI: http://dx.doi.org/10.23977/mediacr.2024.050407.

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