A Telegram Dataset of Propaganda and its Moderation

Abstract

Messaging applications like Telegram have evolved into de facto social networking platforms as they add features like broadcast channels and large groups. Yet, research on these aspects of Telegram is sparse compared to more traditional social media platforms. In this paper, we present a dataset of Telegram messages collected using the export API that returns channel histories, complemented by messages collected in real-time. This dual collection methodology allows us to label deleted messages, i.e., messages that are present in the real-time dataset but not the historical dataset. Additionally, we provide labels indicating whether messages have been sent by accounts belonging to one of two distinct propaganda networks. We provide experiments that show how this rich dataset of Telegram messages can be used to study moderation in Telegram, stances and trends on different topics, and to shed light on malicious behaviours present on Telegram. Finally, we outline other use cases where our dataset could help the research community better understand Telegram as a social network.