A Computational Approach to Analyzing the Twitter Debate on Gaming Disorder

Abstract

The recognition of excessive forms of media entertainment use (such as uncontrolled video gaming or the use of social networking sites) as a disorder is a topic widely discussed among scientists and therapists, but also among politicians, journalists, users, and the industry. In 2018, when the World Health Organization (WHO) decided to include the addictive use of digital games (gaming disorder) as a diagnosis in the International Classification of Diseases, the debate reached a new peak. In the current article, we aim to provide insights into the public debate on gaming disorder by examining data from Twitter for 11 months prior to and 8 months after the WHO decision, analyzing the (change in) topics, actors, and sentiment over time. Automated content analysis revealed that the debate is organic and not driven by spam accounts or other overly active ‘power users.’ The WHO announcement had a major impact on the debate, moving it away from the topics of parenting and child welfare, largely by activating actors from gaming culture. The WHO decision also resulted in a major backlash, increasing negative sentiments within the debate.

Compensatory video gaming. Gaming behaviours and adverse outcomes and the moderating role of stress, social interaction anxiety, and loneliness

“…Both diagnosis instruments define problematic video game use upon a gradual loss of control and self-regulatory mechanisms that likely result in functional impairments (concerning an individual's professional, social, and relational life), eventually leading to addiction (Jo et al 2019). This diagnostic institutionalisation of gaming disorder sparked an intense public debate (Schatto-Eckrodt et al 2020) and harsh criticism from various researchers, who highlighted significant shortcomings of the underlying empirical findings (Griffiths et al 2016) that may lead to an overpathologization of harmless (sometimes even beneficial) activities (Kardefelt-Winther et al 2017). More specifically, it has been argued that such an overpathologization of gaming might create a moral panic through which a majority of healthy gamers may end up stigmatised, potentially culminating in health policies that may involve unnecessary treatments of false-positive cases (Aarseth et al 2017).…”

“Rough Day … Need a Hug”: Learning Challenges and Experiences of the Alzheimer’s Disease and Related Dementia Caregivers on Reddit

“…In comparison to standard topic modeling, STM allows us to incorporate document-level metadata (e.g., authorship and creation time) into the topic modeling to investigate topic prevalence regarding the metadata. STM has been shown to improve inference and qualitative interpretability and is widely adopted in computational social science (Reber 2019;Schatto-Eckrodt, Janzik et al 2020). In this paper, we introduce a boolean metadata variable to indicate whether a submission is posted within ADRD subreddits or non-ADRD subreddits, and investigate how the topics are different in these two types of subreddits.…”