Structural Dynamics of Harmful Content Dissemination on WhatsApp

Abstract

WhatsApp, a platform with over two billion global users, plays a pivotal role in digital communication but also serves as a vector for harmful content such as misinformation, hate speech, and political propaganda. This study examines the dynamics of harmful message dissemination in WhatsApp groups, with a focus on their structural characteristics. Utilizing a comprehensive dataset of over 5.1 million messages—including text, images, and videos—collected from approximately 6,000 groups in India, we reconstruct message propagation cascades to analyze patterns of dissemination. Our findings reveal that harmful messages consistently achieve greater depth and breadth of dissemination compared to normal messages, with videos and images emerging as the primary modes of spread. These results suggest a distinctive dissemination pattern for harmful content. However, our analysis indicates that modality alone cannot fully account for the structural differences in propagation. Finally, using the reconstructed cascades and the spreading patterns, we estimate the potential reach of various types of harmful content. We find that harmful viral content reaches almost 5 times more users compared to normal content. The findings highlight the critical role of structural characteristics in the spread of these harmful messages, suggesting that strategies targeting structural characteristics of message chains could be crucial in managing the dissemination of such content on private messaging platforms.