pytopicgram: A library for data extraction and topic modeling from Telegram channels

Telegram is a popular platform for public communication, generating large amounts of messages through its channels. The library offers key features such as easy message retrieval, detailed channel information, engagement metrics, and topic identification using advanced modeling techniques. By simplifying data extraction and analysis, pytopicgram allows users to understand how content spreads and how audiences interact on Telegram. This paper describes the design, main features, and practical uses of pytopicgram, showcasing its effectiveness for studying public conversations on Telegram. Messaging platforms like Telegram have become critical spaces for information exchange, social mobilization, and digital communities. With features such as public channels, unlimited subscribers, and a degree of anonymity, Telegram has emerged as a valuable source of unstructured data reflecting various social, political, and cultural dynamics [1].