BetXplain: An Explanation-Annotated Dataset for Detecting Manipulative Betting Advertisements on Social Media
arXiv:2606.27274v1 Announce Type: new Abstract: The promotion of betting applications on social media platforms has increased significantly in recent years. Many of these advertisements use persuasive techniques that may mislead users, encourage risky behavior, and potentially influence users' mental well-being. However, research on the automated detection of manipulative and deceptive betting advertisements remains limited due to the lack of publicly available annotated datasets. In this work, we introduce a new dataset of betting-related advertisements collected from two widely used social m
The proliferation of betting advertisements and AI's increasing role in content moderation are converging, making automated detection tools critically relevant for social media platforms.
This development addresses the need for robust methods to identify and mitigate manipulative advertising, impacting user safety and regulatory compliance within the digital advertising ecosystem.
The availability of a new explanation-annotated dataset for manipulative betting ads provides a foundation for more effective AI models for content moderation and platform governance.
- · Social Media Platforms
- · AI/ML Developers
- · Regulatory Bodies
- · Users/Consumers
- · Manipulative Advertisers
- · Illicit Betting Operators
Improved detection of manipulative betting advertisements leads to a cleaner online environment.
Social media platforms enhance brand safety and user trust, potentially influencing ad revenue models and content policies.
This could set a precedent for AI-driven moderation of other problematic content categories, shaping future internet governance and platform liability.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.LG