Unfiltered Conversations: A Dataset of 2024 U.S. Presidential Election Discourse on Truth Social
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866909376125599744 |
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| author | Shah, Kashish Gerard, Patrick Luceri, Luca Ferrara, Emilio |
| author_facet | Shah, Kashish Gerard, Patrick Luceri, Luca Ferrara, Emilio |
| contents | Truth Social, launched as a social media platform with a focus on free speech, has become a prominent space for political discourse, attracting a user base with diverse, yet often conservative, viewpoints. As an emerging platform with minimal content moderation, Truth Social has facilitated discussions around contentious social and political issues but has also seen the spread of conspiratorial and hyper-partisan narratives. In this paper, we introduce and release a comprehensive dataset capturing activity on Truth Social related to the upcoming 2024 U.S. Presidential Election, including posts, replies, user interactions, content and media. This dataset comprises 1.5 million posts published between February, 2024 and October 2024, and encompasses key user engagement features and posts metadata. Data collection began in June 2024, though it includes posts published earlier, with the oldest post dating back to February 2022. This offers researchers a unique resource to study communication patterns, the formation of online communities, and the dissemination of information within Truth Social in the run-up to the election. By providing an in-depth view of Truth Social's user dynamics and content distribution, this dataset aims to support further research on political discourse within an alt-tech social media platform. The dataset is publicly available at https://github.com/kashish-s/TruthSocial_2024ElectionInitiative |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_01330 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Unfiltered Conversations: A Dataset of 2024 U.S. Presidential Election Discourse on Truth Social Shah, Kashish Gerard, Patrick Luceri, Luca Ferrara, Emilio Social and Information Networks Truth Social, launched as a social media platform with a focus on free speech, has become a prominent space for political discourse, attracting a user base with diverse, yet often conservative, viewpoints. As an emerging platform with minimal content moderation, Truth Social has facilitated discussions around contentious social and political issues but has also seen the spread of conspiratorial and hyper-partisan narratives. In this paper, we introduce and release a comprehensive dataset capturing activity on Truth Social related to the upcoming 2024 U.S. Presidential Election, including posts, replies, user interactions, content and media. This dataset comprises 1.5 million posts published between February, 2024 and October 2024, and encompasses key user engagement features and posts metadata. Data collection began in June 2024, though it includes posts published earlier, with the oldest post dating back to February 2022. This offers researchers a unique resource to study communication patterns, the formation of online communities, and the dissemination of information within Truth Social in the run-up to the election. By providing an in-depth view of Truth Social's user dynamics and content distribution, this dataset aims to support further research on political discourse within an alt-tech social media platform. The dataset is publicly available at https://github.com/kashish-s/TruthSocial_2024ElectionInitiative |
| title | Unfiltered Conversations: A Dataset of 2024 U.S. Presidential Election Discourse on Truth Social |
| topic | Social and Information Networks |
| url | https://arxiv.org/abs/2411.01330 |