Exploring Left-Wing Extremism on the Decentralized Web: An Analysis of Lemmygrad.ml
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arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| author | Balci, Utkucan Sirivianos, Michael Blackburn, Jeremy |
| author_facet | Balci, Utkucan Sirivianos, Michael Blackburn, Jeremy |
| contents | This study investigates the presence of left-wing extremism on the Lemmygrad.ml instance of the decentralized social media platform Lemmy, from its launch in 2019 up to a month after the bans of the subreddits r/GenZedong and r/GenZhou. We conduct a temporal analysis on Lemmygrad.ml's user activity, with also measuring the degree of highly abusive or hateful content. Furthermore, we explore the content of their posts using a transformer-based topic modeling approach. Our findings reveal a substantial increase in user activity and toxicity levels following the migration of these subreddits to Lemmygrad.ml. We also identify posts that support authoritarian regimes, endorse the Russian invasion of Ukraine, and feature anti-Zionist and antisemitic content. Overall, our findings contribute to a more nuanced understanding of political extremism within decentralized social networks and emphasize the necessity of analyzing both ends of the political spectrum in research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_23699 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Exploring Left-Wing Extremism on the Decentralized Web: An Analysis of Lemmygrad.ml Balci, Utkucan Sirivianos, Michael Blackburn, Jeremy Social and Information Networks This study investigates the presence of left-wing extremism on the Lemmygrad.ml instance of the decentralized social media platform Lemmy, from its launch in 2019 up to a month after the bans of the subreddits r/GenZedong and r/GenZhou. We conduct a temporal analysis on Lemmygrad.ml's user activity, with also measuring the degree of highly abusive or hateful content. Furthermore, we explore the content of their posts using a transformer-based topic modeling approach. Our findings reveal a substantial increase in user activity and toxicity levels following the migration of these subreddits to Lemmygrad.ml. We also identify posts that support authoritarian regimes, endorse the Russian invasion of Ukraine, and feature anti-Zionist and antisemitic content. Overall, our findings contribute to a more nuanced understanding of political extremism within decentralized social networks and emphasize the necessity of analyzing both ends of the political spectrum in research. |
| title | Exploring Left-Wing Extremism on the Decentralized Web: An Analysis of Lemmygrad.ml |
| topic | Social and Information Networks |
| url | https://arxiv.org/abs/2507.23699 |