Abstract

The present study explored the topics and sentiment associated with gambling addiction during the COVID-19 pandemic, using topic modeling and sentiment analysis on tweets in English posted between 17-24^th April 2020. The study was exploratory in nature, with its main objective consisting of inductively identifying topics embedded in user-generated content. We found that a five-topic model was the best in representing the data corpus, including: (i) the public’s perception of gambling addiction amid the COVID-19 outbreak, (ii) risks and support available for those who stay at home, (iii) the users’ interpretation of gambling addiction, (iv) forms of gambling during the pandemic, and (v) gambling advertising and impact on families. Sentiment analysis showed a prevalence of underlying fear, trust, sadness, and anger, across the corpus. Users viewed the pandemic as a driver of problematic gambling behaviors, possibly exposing unprepared individuals and communities to forms of online gambling, with potential long-term consequences and a significant impact on health systems. Despite the limitations of the study, we hypothesize that enhancing the presence of mental health operators and practitioners treating problem gambling on social media might positively impact public mental health and help prevent health services from being overwhelmed, in times when healthcare resources are limited.

摘要

本研究使用主题建模和情感分析对 17 至 24^日之间发布的英文推文，探讨了 COVID-19 大流行期间与赌博成瘾相关的主题和情感2020 年 4 月。该研究本质上是探索性的，其主要目标包括归纳识别嵌入在用户生成内容中的主题。我们发现五个主题的模型最能代表数据语料库，包括：(i) 在 COVID-19 爆发期间公众对赌博成瘾的看法，(ii) 呆在家里的人可获得的风险和支持，( iii) 用户对赌博成瘾的解释，(iv) 大流行期间的赌博形式，以及 (v) 赌博广告和对家庭的影响。情绪分析表明，整个语料库中普遍存在潜在的恐惧、信任、悲伤和愤怒。用户将大流行视为有问题的赌博行为的驱动因素，可能使毫无准备的个人和社区暴露于各种形式的在线赌博中，具有潜在的长期后果并对卫生系统产生重大影响。尽管该研究存在局限性，但我们假设，在医疗资源有限的时候，加强心理健康运营商和从业者在社交媒体上治疗问题赌博的存在可能会对公共心理健康产生积极影响，并有助于防止医疗服务不堪重负。