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Hate Speech on Social Media ; Discours de haine dans les réseaux socionumériques
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In: ISSN: 0243-6450 ; EISSN: 1960-6001 ; Mots: les langages du politique ; https://hal.archives-ouvertes.fr/hal-03137170 ; Mots: les langages du politique, 125, E.N.S. Editions, 2021, 9791036203060 (2021)
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REVIEW: Thurlow Crispin, Dürscheid Christa & Diémoz Federica (eds) (2020). Visualizing digital discourse. Berlin/Boston: De Gruyter.
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In: https://hal.archives-ouvertes.fr/hal-03218125 ; 2021 (2021)
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Brand conversation: Linguistic practices on social media in the light of face-work theory
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In: ISSN: 2051-5707 ; Recherche et Applications en Marketing (English Edition) ; https://hal.archives-ouvertes.fr/hal-03049134 ; Recherche et Applications en Marketing (English Edition), SAGE Publications, 2021, ⟨10.1177/2051570720974511⟩ (2021)
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Brand conversation: Linguistic practices on social media in the light of face-work theory ; La conversation de marque : pratiques linguistiques sur les médias sociaux selon la théorie du face-work
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In: Recherches et applications en Marketing ; https://hal.archives-ouvertes.fr/hal-03021314 ; Recherches et applications en Marketing, 2021, ⟨10.1177/0767370120962610⟩ (2021)
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Edmodo au service de la productivité écrite et interactionnelle des apprenants de FLE
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In: Sprache und Fremdsprachenunterricht - Magie durch Produktivität ; https://hal-univ-lyon3.archives-ouvertes.fr/hal-03171996 ; Sprache und Fremdsprachenunterricht - Magie durch Produktivität, 12, htw saar Saarbrücken, 2021, Saarbrücken Series on Linguistics and Language Methodology (SSLLM), 978-3-942949-32-3 ; https://drive.google.com/file/d/18boFxO7vyUNEHbIo2qPcEc1ur7di53E-/view (2021)
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Der Elfenbeinturm hat Fenster. Browserfenster : Wissenschaftskommunikation in sozialen Medien [Online resource]
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In: Workshop Neue Formate in der Wissenschaftskommunikation - Herausforderung für die Informationsversorgung? (2021), 1-36
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Linguistik-Repository
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Personality Ontology Corpus for Indonesian Social Media Text ...
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Personality Ontology Corpus for Indonesian Social Media Text ...
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Predicting First Dates from Language Style Matching in Online Dating Messages ...
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Predicting emotional links between genre, plot, and reader response ...
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Social media users’ crisis response: A lexical exploration of social media content in an international sport crisis
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In: Research outputs 2014 to 2021 (2021)
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Impact of social media data on postmarket safety evaluation of medicines: a literature review on automatic mining initiatives of adverse drug reactions
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The Telegram Chronicles of Online Harm
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In: Journal of Open Humanities Data; Vol 7 (2021); 8 ; 2059-481X (2021)
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A Telegram Corpus for Hate Speech, Offensive Language, and Online Harm
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In: Journal of Open Humanities Data; Vol 7 (2021); 9 ; 2059-481X (2021)
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The Challenges of Digital Diplomacy in the Era of Globalization: The Case of the United Arab Emirates
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In: International Journal of Communication; Vol 15 (2021); 19 ; 1932-8036 (2021)
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A Survey on Multilingual Hate Speech Detection and Classification by Machine Learning Techniques ...
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Abstract:
Abstract: It is critical to identify hate speech on social media. The Spread of uncontrolled hate can damage society, marginalized people, or groups. Social media plays a significant role in hate speech spreading online. Due to paralinguistic posts (e.g., emotions, hashtags) in social media, it is difficult to detect automatically in which it contains plenty of poorly written text. That provides automatic results for hate speech detection, several pieces of research were introduced ranges from simple to complex deep neural networks models. This paper proposes background detection of hate speech. Furthermore, anti-social behaviour topics and recent contributions of hate speech are reviewed. Finally, issues and recommendations of hate speech detections are explained in detail. ...
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Keyword:
Hate speech, social media, machine learning, deep neural network models, multilingual
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URL: https://dx.doi.org/10.5281/zenodo.5599744 https://zenodo.org/record/5599744
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