A Telegram Corpus for Hate Speech, Offensive Language, and Online Harm
We provide a new text corpus from the social medium Telegram, which is rich in indirect forms of divisive speech. We scraped all messages from one channel of Donald Trump supporters, covering a large part of his presidency, from late 2016 until January 2021, including the January 6 Capitol riot. The...
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| Format: | Article |
| Language: | English |
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Ubiquity Press
2021-07-01
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| Series: | Journal of Open Humanities Data |
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| Online Access: | https://openhumanitiesdata.metajnl.com/articles/32 |
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| author | Veronika Solopova Tatjana Scheffler Mihaela Popa-Wyatt |
| author_facet | Veronika Solopova Tatjana Scheffler Mihaela Popa-Wyatt |
| author_sort | Veronika Solopova |
| collection | DOAJ |
| description | We provide a new text corpus from the social medium Telegram, which is rich in indirect forms of divisive speech. We scraped all messages from one channel of Donald Trump supporters, covering a large part of his presidency, from late 2016 until January 2021, including the January 6 Capitol riot. The discussion among the group members, over this long time period, includes the spread of disinformation, disparaging of out-group members, and other forms of harmful speech. To enable research into the role of harmful speech in political discourse, we added two types of annotations to the corpus: (i) automatic annotations of offensive language for all messages, and (ii) our own manual annotations of harmful language for a portion of the posts leading up to the January 2021 Capitol riot and its aftermath. |
| format | Article |
| id | doaj-art-58541c8d46504e4e8d13e4cc7191b57f |
| institution | OA Journals |
| issn | 2059-481X |
| language | English |
| publishDate | 2021-07-01 |
| publisher | Ubiquity Press |
| record_format | Article |
| series | Journal of Open Humanities Data |
| spelling | doaj-art-58541c8d46504e4e8d13e4cc7191b57f2025-08-20T02:18:55ZengUbiquity PressJournal of Open Humanities Data2059-481X2021-07-01710.5334/johd.3228A Telegram Corpus for Hate Speech, Offensive Language, and Online HarmVeronika Solopova0Tatjana Scheffler1Mihaela Popa-Wyatt2Freie Universität BerlinRuhr-Universität BochumLeibniz-Zentrum Allgemeine Sprachwissenschaft, BerlinWe provide a new text corpus from the social medium Telegram, which is rich in indirect forms of divisive speech. We scraped all messages from one channel of Donald Trump supporters, covering a large part of his presidency, from late 2016 until January 2021, including the January 6 Capitol riot. The discussion among the group members, over this long time period, includes the spread of disinformation, disparaging of out-group members, and other forms of harmful speech. To enable research into the role of harmful speech in political discourse, we added two types of annotations to the corpus: (i) automatic annotations of offensive language for all messages, and (ii) our own manual annotations of harmful language for a portion of the posts leading up to the January 2021 Capitol riot and its aftermath.https://openhumanitiesdata.metajnl.com/articles/32social mediaoffensive languageharmful speechlinguisticsphilosophy |
| spellingShingle | Veronika Solopova Tatjana Scheffler Mihaela Popa-Wyatt A Telegram Corpus for Hate Speech, Offensive Language, and Online Harm Journal of Open Humanities Data social media offensive language harmful speech linguistics philosophy |
| title | A Telegram Corpus for Hate Speech, Offensive Language, and Online Harm |
| title_full | A Telegram Corpus for Hate Speech, Offensive Language, and Online Harm |
| title_fullStr | A Telegram Corpus for Hate Speech, Offensive Language, and Online Harm |
| title_full_unstemmed | A Telegram Corpus for Hate Speech, Offensive Language, and Online Harm |
| title_short | A Telegram Corpus for Hate Speech, Offensive Language, and Online Harm |
| title_sort | telegram corpus for hate speech offensive language and online harm |
| topic | social media offensive language harmful speech linguistics philosophy |
| url | https://openhumanitiesdata.metajnl.com/articles/32 |
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