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Cognella Academic Publishing, Illinois State University"}],"container-title":["Social Network Analysis and Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13278-026-01632-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13278-026-01632-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13278-026-01632-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T06:17:25Z","timestamp":1787984245000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13278-026-01632-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,7]]},"references-count":60,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["1632"],"URL":"https:\/\/doi.org\/10.1007\/s13278-026-01632-1","relation":{},"ISSN":["1869-5469"],"issn-type":[{"value":"1869-5469","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,7]]},"assertion":[{"value":"28 May 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 July 2026","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 July 2026","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 August 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no conflict of interest.","order":1,"name":"Ethics","label":"Conflict of interest","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study draws exclusively on publicly available, anonymised user-generated content and involves no intervention with human participants; it therefore did not require ethics-board approval.","order":2,"name":"Ethics","label":"Ethics approval","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All data consist of publicly available YouTube comments and video transcripts. Usernames and other identifying information were removed prior to annotation and analysis and the corpus is released in anonymised form only, such that individual users cannot be identified from it.","order":3,"name":"Ethics","label":"Data collection and privacy","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"To mitigate annotators fatigue and distress, sessions were structured with regular consensus meetings, which also served as a venue for annotators to flag distressing material. Annotators were informed of the nature of the content beforehand and fairly compensated.","order":4,"name":"Ethics","label":"Annotator welfare","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The released dataset and models are intended to support computational social science, platform-governance, and media-literacy research. As with any detector of political speech, they carry dual-use risks: they could in principle be repurposed to suppress legitimate expression, or to optimise rather than detect divisive rhetoric. We release them for research use with documentation of their intended scope and known limitations, and encourage critical assessment prior to any downstream deployment.","order":5,"name":"Ethics","label":"Dual-use considerations","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"73"}}