Sentiment and Topic Modeling Analysis on Twitter Reveals Concerns over Cannabis-Containing Food after Cannabis Legalization in Thailand

Abstract

Objectives Twitter has been used to express a diverse range of public opinions about cannabis legalization in Thailand. The purpose of this study was to observe changes in sentiments after cannabis legalization and to investigate health-related topics discussed on Twitter. Methods Tweets in Thai and English related to cannabis were scraped from Twitter between May 1 and June 13, 2022, during cannabis legalization in Thailand. Sentiment and topic-modeling analyses were used to compare the content of tweets before and after legalization. Health-related topics were manually grouped into categories by their content and rated according to the number of corresponding tweets. Results We collected 21,242 and 6,493 tweets, respectively, for Thai and English search terms. A sharp increase in the number of tweets related to cannabis legalization was detected at the time of its public announcement. Sentiment analysis in the Thai search group showed a significant change (p < 0.0001) in sentiment distribution after legalization, with increased negative and decreased positive sentiments. A significant change was not found in the English search group (p = 0.4437). Regarding cannabis-containing food as a leading issue, topic-modeling analysis revealed public concerns after legalization in the Thai search group, but not the English one. Topics related to cannabis tourism surfaced only in the English search group. Conclusions Since cannabis legalization, the primary health-related concern has been cannabis-containing food. Education and clear regulations on cannabis use are required to strengthen oversight of cannabis in the Thai population, as well as among medical tourists.

Keywords

• cannabis
• legislation
• social media
• sentiment analysis
• thailand