Adapting in times of crisis
How social media marketing of gambling changed in response to major shifts in the gambling landscape
Bibliographic Data
| ID | 20510252 |
|---|---|
| Authors | Scott Houghton (0000-0003-0165-122X, Northumbria University, corresponding author), Frédéric Boy (0000-0003-1373-6634, Swansea University), Alexander Bradley (0000-0003-4304-7653, University of Portsmouth), Richard J E James (0000-0002-6644-7011, University of Nottingham), Heather Wardle (0000-0003-1361-3706, University of Glasgow), Simon Dymond (0000-0003-1319-4492, Swansea University) |
| Year | 2025 |
| Pages | 1-17 |
| Publication date | 2025-10-13 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Information Communication & Society (JOURNAL) |
| Journal identifiers | ISSN: 1369-118X • E-ISSN: 1468-4462 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/1369118x.2025.2572025 |
| OpenAlex | W4415137281 |
| Language | EN |
| References cited | 38 |
Gambling marketing on social media in countries like Great Britain (GB) is relatively well understood. Little is known, however, about how such marketing is impacted by major changes to the gambling landscape, like the COVID-19 pandemic. Here, we assessed changes in the frequency, sentiment, and content of gambling marketing on Twitter by Great Britain (GB) gambling operators and affiliates. We analysed n = 353,134 tweets from 10 operators and affiliates posted between January 2020 and July 2022. Using machine learning, we categorised tweets based on content and tracked how social media use by operators and affiliates changed during the pandemic. Findings revealed decreases in the frequency of tweets posted during the first national lockdown, particularly for affiliates, and a greater proportion of sports content related tweets, compared to direct advertising, as the pandemic continued. Postings by affiliates tended to include more positive sentiments. Our findings highlight the speed at which gambling operators and affiliates adapted their social media marketing campaigns to large structural changes like the COVID-19 lockdowns
Consumer behaviour · Perception · Social media · The Internet · Cybercrime and Law Enforcement Studies · FinTech, Crowdfunding, Digital Finance · Gambling Behavior and Treatments
Machine learning in automated text categorization
Tracking online searches for gambling activities and operators in the United Kingdom during the Covid-19 pandemic
Comparing football bettors' response to social media marketing differing in bet complexity and account type – An experimental study
Engagement with Social Media and Social Media Advertising
Covid-19, lockdowns and well-being
The impact of the Covid-19 pandemic on the use of social media
| Highly cited | No |
|---|