The Adaptive Tactics of Online Gambling Promotion: Exploiting Viral Content Algorithms
The Ministry of Communication and Digital Affairs has recorded a 128 percent surge in spam comments containing online gambling content compared to the average findings from January to June 2026. The modus operandi behind it has also shifted. It is no longer individuals typing one by one, but automated bot networks specifically targeting accounts with high interaction, ranging from government agency accounts, mass media, to influencers. This data should serve as an alarm, not only for authorities combating online gambling, but also for how we understand the inner workings of social media.
Public discourse on online gambling has so far revolved around two poles. The first pole is the government’s claim of success. The Financial Transaction Reports and Analysis Centre noted that after continuously increasing since 2017 to reach Rp359.81 trillion in 2024, the turnover value of online gambling funds finally fell by 20 percent in 2025 to Rp286.84 trillion. The second pole is the narrative of victims. Minister of Communication and Digital Affairs Meutya Hafid stated that nearly 200,000 Indonesian children have been exposed to online gambling, with around 80,000 of them under the age of 10.
Between these two poles lies a mechanism rarely discussed openly. Social media algorithms, designed to maximise user interaction, have inadvertently become a channel that benefits the spread of online gambling promotions.
Recommendation algorithms on social media platforms essentially have one main goal: to retain user attention for as long as possible. One of the most common signals used to assess whether a post deserves wider recommendation is the amount of interaction it receives, including the number of comments. This logic is inherently neutral. The algorithm does not distinguish whether the comments originate from organic discussion or from bot networks deliberately flooding the comment section with links to gambling sites.
Imagine a rebroadcast post of a football match flooded with a large number of comments. The algorithm system will read this phenomenon as an indication that the content is in demand. The content then has the potential to be pushed to appear more widely on other users’ timelines. At this point, online gambling spam gains a structural advantage that no one planned, including the platform companies themselves. The algorithm does not consciously take sides, but the end result still benefits those spreading illegal content. This is where engagement becomes an unwitting ally.
This algorithmic loophole is becoming increasingly difficult to close because online gambling operators continue to refine their methods of deceiving the system. Meta has revealed that online gambling networks are constantly developing new ways to evade automatic detection systems. Besides using coded words to replace standard terms like gambling or slots, perpetrators also utilise comment sections as a channel to direct users to gambling sites. This method technically circumvents content moderation systems that still largely rely on keyword matching. As long as the database of prohibited words is not dynamically updated, such coded words will continue to slip through.
A similar pattern is also evident on the other side of the online gambling ecosystem, namely in its fund flows. Financial authorities note that transactions are now shifting to more dispersed and smaller nominal patterns, making them harder to trace. This demonstrates a common strategy between content disseminators and fund managers, both adapting to evade existing detection systems, whether keyword-based detection on social media or transaction pattern-based detection in the financial sector.
This rapid adaptation then exposes a capacity gap between regulators and automated systems. On one hand, the regulatory approach remains manual and reactive, such as deleting content one by one or blocking accounts after reports are received. On the other hand, the spam dissemination system already operates on a fully automated scale. Bots can produce thousands of comments in minutes, while simultaneously exploiting algorithmic loopholes designed for entirely different purposes.
This situation demands an expansion of the responsibility framework, not only for law enforcement and financial authorities, but also for digital platform operators. This responsibility does not mean accusing platforms of deliberately facilitating online gambling, but rather pushing for transparency and accountability over how recommendation systems work, particularly during moments of predictably high traffic surges, such as major sporting tournaments.
The 128 percent surge in spam should not be read merely as a statistical figure. That number is an indicator that the online gambling problem in Indonesia has shifted, from merely an issue of law enforcement and digital literacy, to a problem of the technological architecture itself. As long as the algorithm system still judges the noise of interaction as the sole measure of content quality, without considering the origin of that interaction, the digital space will continue to provide loopholes for parties exploiting it for illegal purposes. The algorithm does not care whether a comment was born from genuine discussion or from an online gambling bot programmed to flood the section; the system only cares about who is the loudest. As long as that remains the metric, online gambling will always have an ally that never even realises it is helping.