Understanding Illicit Promotional Content on Short Video Platform

Abstract

With the rapid expansion of wireless infrastructure and smart devices, short video platforms have become a staple of modern digital ecosystems, offering convenience but also introducing new risks. One such risk is illicit promotional content (IPC), which encompasses deceptive or fraudulent material intended to promote products, services, or events in violation of platform policies. As these platforms grow in popularity, so too does the threat of IPC, which has adapted to the short video format, referred to here as Short Video-Illicit Promotional Content (SVIPC). The detection of SV-IPC is crucial to protect users, especially minors, from fraudulent schemes and harmful material. Current detection approaches primarily rely on image processing, text analysis, and QR code detection, limiting their effectiveness on short video platforms. This paper provides a comprehensive investigation into SV-IPC and its evasion techniques, revealing the underlying ecosystem of illicit promotion. To address these challenges, we introduce a hybrid detection framework that integrates natural language processing with video analysis. Extensive experiments conducted on Chinese TikTok validate the proposed scheme, demonstrating high effectiveness with an F1-score of 90.7%, recall of 90.3%, and precision of 91.2%. This study underscores the broader societal implications of SV-IPC and the importance of enhanced detection mechanisms.