@article{,
title= {Unearthing a Billion Telegram Posts about the 2024 U.S. Presidential Election: Development of a Public Dataset (v2)},
journal= {},
author= {Leonardo Blas, Luca Luceri, Emilio Ferrara},
year= {},
url= {https://arxiv.org/abs/2410.23638},
abstract= {With its lenient moderation policies and long-standing associations with potentially unlawful activities, Telegram has become an incubator for problematic content, frequently featuring conspiratorial, hyper-partisan, and fringe narratives. In the political sphere, these concerns are amplified by reports of Telegram channels being used to organize violent acts, such as those that occurred during the Capitol Hill attack on January 6, 2021. As the 2024 U.S. election approaches, Telegram remains a focal arena for societal and political discourse, warranting close attention from the research community, regulators, and the media. Based on these premises, we introduce and release a Telegram dataset focused on the 2024 U.S. Presidential Election, featuring over 30,000 chats and half a billion messages, including chat details, profile pictures, messages, and user information. We constructed a network of chats and analyzed the 500 most central ones, examining their shared messages. This resource represents the largest public Telegram dataset to date, offering an unprecedented opportunity to study political discussion on Telegram in the lead-up to the 2024 U.S. election. We will continue to collect data until the end of 2024, and routinely update the dataset released at: https://github.com/leonardo-blas/usc-tg-24-us-election.},
keywords= {US 2024 Election, Telegram},
terms= {This dataset is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License (CC BY-NC-SA 4.0). By using this dataset, you agree to abide by the stipulations in the license and cite the following manuscript:
Leonardo Blas, Luca Luceri, and Emilio Ferrara. Unearthing a Billion Telegram Posts about the 2024 U.S. Presidential Election: Development of a Public Dataset. 2024. arXiv, https://arxiv.org/abs/2410.23638.},
license= {https://creativecommons.org/licenses/by-nc-sa/4.0/},
superseded= {}
}