pytopicgram: A library for data extraction and topic modeling from Telegram channels
File(s)
Published version
Author(s)
Gómez-Romero, Juan
Correa, Javier Cantón
Mercado, Rubén Pérez
Abad, Francisco Prados
Molina-Solana, Miguel
Type
Journal Article
Abstract
Telegram is a popular platform for communication, generating large volumes of messages through its open channels. pytopicgram is a Python library designed to help researchers efficiently collect, organize, and analyze Telegram messages, addressing the increasing demand to understand online discourse. Key functionalities include efficient message retrieval, computation of engagement metrics, and advanced topic modeling. By automating the data extraction and analysis pipeline, pytopicgram simplifies the investigation of how content spreads, how topics evolve, and how audiences interact on Telegram. The library’s modular architecture ensures flexibility and scalability, making it suitable for diverse applications. This paper describes the design, main features, and illustrative examples that demonstrate pytopicgram’s practical effectiveness for studying public conversations.
Date Issued
2025-05-01
Date Acceptance
2025-03-21
Citation
SoftwareX, 2025, 30
ISSN
2352-7110
Publisher
Elsevier BV
Journal / Book Title
SoftwareX
Volume
30
Copyright Statement
© 2025 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/b
License URL
Publication Status
Published
Article Number
102141
Date Publish Online
2025-04-02