Using LDA Topic Modeling to Understand Regrowth Factors of the Chinese Gaming Industry in the COVID-19 Era: Current Situation, Future and Predicament
DOI:
https://doi.org/10.13052/jwe1540-9589.2233Keywords:
Topic modeling, games industry, COVID-19, Text Mining, Latent Dirichlet Allocation, news textAbstract
The gaming industry, which was among the industries least affected by the COVID-19 outbreak, exhibited positive growth trends during the COVID-19 period. This paper explores the impact of COVID-19 on the gaming industry by analyzing news texts from 2020 to 2022 using text mining and LDA (latent Dirichlet allocation) topic classification, and visualizing charts. The study focuses on three themes, namely the current situation, the future, and possible problems of China’s game industry in the post-epidemic era.
The findings of this study suggest that the development of the game industry during the COVID-19 outbreak prompted the government to regulate policies and promote the transformation of game companies, which had a positive impact on the development of China’s game industry. However, this study also found that due to the effects of COVID-19, society and the government have increased their focus on the time management of underage game users, which poses a significant challenge to the games industry.
This paper recommends improvements from three perspectives, namely society, policy, and enterprise, with the aim of contributing to the long-term development of China’s game industry.
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