2023
DOI: 10.1007/s13278-023-01061-4
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Unsupervised fine-grained hate speech target community detection and characterisation on social media

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Cited by 6 publications
(5 citation statements)
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“…These findings highlight diverse avenues for effectively detecting hate speech, underscoring the need for continued research to address evolving trends and promote online safety. The projects conducted by [3] and [7] are considered a valuable starting point, approaching the problem with different NLP and AI techniques.…”
Section: Related Workmentioning
confidence: 99%
See 3 more Smart Citations
“…These findings highlight diverse avenues for effectively detecting hate speech, underscoring the need for continued research to address evolving trends and promote online safety. The projects conducted by [3] and [7] are considered a valuable starting point, approaching the problem with different NLP and AI techniques.…”
Section: Related Workmentioning
confidence: 99%
“…Hate incidents have been on the rise, fuelled by factors like migration, economic crises, anti-gender narratives, and conspiracy theories, especially during the COVID-19 pandemic, with relevant impacts on freedom of expression and democratic participation. To combat this, international institutions like the European Commission 3 , the Council of Europe 4 , the United Nations and its member states have been working to define and address hate speech and hate crime [12]. Despite the adoption of AI tools for moderation, automated systems have proven insufficient, and further efforts are needed to effectively tackle online hate speech [2,3,7].…”
Section: Introductionmentioning
confidence: 99%
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“…Therefore, social networks function as amplifiers when the objective is to wage a cultural war (Larsson 2020). In this context, our focus is on hate speech as a technique that employs hate rhetoric as a synonym for freedom of expression and portrays political correctness as an analogy to censorship (Aguilar 2023, Amores et al 2021, Hernandez Urbano et al 2021, Lee and Lee 2023, Nguyen et al 2023, Ollagnier et al 2023, Paz, Mayagoitia-Soria and González-Aguilar 2021, Weimann and Masri 2023.…”
Section: Introductionmentioning
confidence: 99%