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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 6 7 8...109 Hits 61 – 80 of 2.170 61 Can high school students check the veracity of information about COVID-19? A case study on critical media literacy in Brazilian ESL classes Meyrer, Karin Paola; Frank Kersch, Dorotea In: Journal of Media Literacy Education (2022) BASE Show details 62 Impact of maternal smartphone use on language output Casar, Mercedes. - 2022 BASE Show details 63 Russia-My History: The Amazing Transformations of a History Exhibit in Post-Crimean Russia Parker, Alina In: Doctoral Dissertations (2022) BASE Show details 64 Alt-Education: Gender, language, and education across the right Tebaldi, Catherine In: Doctoral Dissertations (2022) BASE Show details 65 Booktokers: Generar y compartir contenidos sobre libros a través de TikTok Guiñez Cabrera, Nataly; Mansilla Obando, Katherine In: Comunicar: Revista científica iberoamericana de comunicación y educación, ISSN 1134-3478, Nº 71, 2022 (Ejemplar dedicado a: Discursos de odio en comunicación: Investigaciones y propuestas), pags. 119-130 (2022) BASE Show details 66 La trata de personas en Twitter: Finalidades, actores y temas en la escena hispanohablante Sierra Rodríguez, Alba; Arroyo Machado, Wenceslao; Barroso Hurtado, Domingo In: Comunicar: Revista científica iberoamericana de comunicación y educación, ISSN 1134-3478, Nº 71, 2022 (Ejemplar dedicado a: Discursos de odio en comunicación: Investigaciones y propuestas), pags. 79-91 (2022) BASE Show details 67 Temporal Emotion Dynamics in Social Networks Naskar, Debashis. - : Universitat Politècnica de València, 2022 BASE Show details 68 Partenariat rémunéré entre une entreprise et une influenceuse sur les réseaux sociaux : entrecroisement des voix des femmes autour de l’alimentation des nourrissons Bayard, Chantal; Charton, Laurence In: Nouvelle Revue Synergies Canada; No. 15 (2022): La notion de « voix » en sociolinguistique et sciences sociales ; 2292-2261 (2022) BASE Show details 69 “One does not simply categorize a meme”: A dual classification system for visual-textual internet memes Cochrane, Leslie; Johnson, Alexandra; Lay, Aubrey... In: Proceedings of the Linguistic Society of America; Vol 7, No 1 (2022): Proceedings of the Linguistic Society of America; 5260 ; 2473-8689 (2022) BASE Show details 70 Comunicazione, dibattito pubblico, social media : come orientarsi con la linguistica Pietrandrea, Paola. - Roma : Carocci editore, 2021 BLLDB UB Frankfurt Linguistik Show details 71 AI critiques in the press Crépel, Maxime; Cardon, Dominique; De Mourat, Robin... In: https://hal.archives-ouvertes.fr/hal-03384123 ; 2021 (2021) BASE Show details 72 National Identity Attachment and Its Variables Windari, Tri In: Journal of International Women's Studies (2021) BASE Show details 73 Language modeling for personality prediction Cutler, Andrew. - 2021 BASE Show details 74 Leading the Nation Through Social Media: Jacinda Ardern’s Self-Presentation on Facebook During the COVID-19 Crisis Huang, Lei. - : Auckland University of Technology, 2021 BASE Show details 75 The Rhetoric of Psychopathology: An Interdisciplinary Approach to Understanding and Talking About Mental Health Stigall, Regan. - 2021 BASE Show details 76 Brazilian left-wing activists on Facebook: the role of cultural events in political participation Figeac, Julien; Paton, Nathalie; Peralva, Angelina... In: EISSN: 2245-4373 ; Brasiliana: Journal for Brazilian Studies ; https://halshs.archives-ouvertes.fr/halshs-03366403 ; Brasiliana: Journal for Brazilian Studies, King's College London, 2021, 10 (1), pp.261-284. ⟨10.25160/bjbs.v10i1.125719⟩ ; https://tidsskrift.dk/bras/article/view/125719 (2021) BASE Show details 77 "Un-Canceling" America Barnhizer, David In: Law Faculty Books (2021) BASE Show details 78 An Approach Utilizing Linguistic Features for Fake News Detection Kasseropoulos, Dimitrios,; Tjortjis, Christos In: IFIP Advances in Information and Communication Technology ; 17th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI) ; https://hal.inria.fr/hal-03287679 ; 17th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Jun 2021, Hersonissos, Crete, Greece. pp.646-658, ⟨10.1007/978-3-030-79150-6_51⟩ (2021) BASE Show details 79 Emotionally Informed Hate Speech Detection: A Multi-target Perspective Chiril, Patricia; Pamungkas, Endang Wahyu; Benamara, Farah... In: ISSN: 1866-9956 ; EISSN: 1866-9964 ; Cognitive Computation ; https://hal.archives-ouvertes.fr/hal-03275549 ; Cognitive Computation, Springer, 2021, 13 (4), ⟨10.1007/s12559-021-09862-5⟩ ; https://link.springer.com/article/10.1007%2Fs12559-021-09862-5 (2021) BASE Show details 80 Multiword Expression Features for Automatic Hate Speech Detection Zampieri, Nicolas; Illina, Irina; Fohr, Dominique In: NLDB 2021 - 26th International Conference on Natural Language & Information Systems ; https://hal.archives-ouvertes.fr/hal-03231047 ; NLDB 2021 - 26th International Conference on Natural Language & Information Systems, Jun 2021, Saarbrücken/Virtual, Germany ; http://nldb2021.sb.dfki.de/ (2021) Abstract: International audience ; The task of automatically detecting hate speech in social media is gaining more and more attention. Given the enormous volume of content posted daily, human monitoring of hate speech is unfeasible. In this work, we propose new word-level features for automatic hate speech detection (HSD): multiword expressions (MWEs). MWEs are lexical units greater than a word that have idiomatic and compositional meanings. We propose to integrate MWE features in a deep neural network-based HSD framework. Our baseline HSD system relies on Universal Sentence Encoder (USE). To incorporate MWE features, we create a three-branch deep neural network: one branch for USE, one for MWE categories, and one for MWE embeddings. We conduct experiments on two hate speech tweet corpora with different MWE categories and with two types of MWE embeddings, word2vec and BERT. Our experiments demonstrate that the proposed HSD system with MWE features significantly outperforms the baseline system in terms of macro-F1. Keyword: [INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; [INFO]Computer Science [cs]; Deep learning; Hate speech detection; Social media URL: https://hal.archives-ouvertes.fr/hal-03231047/file/NLDB_2021___Multiword_Expression_Features_for_Automatic_Hate_Speech_Detection__short_paper___.pdf https://hal.archives-ouvertes.fr/hal-03231047/document https://hal.archives-ouvertes.fr/hal-03231047 BASE Hide details Page: 1 2 3 4 5 6 7 8...109

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