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(Re)defining the Political Opposition: A Corpus-based Critical Discourse Analysis of Urban Dictionary Definitions of Political Identities
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Discursive analysis of remarks deemed sexist, misogynistic in a media context ; Analyse discursive de propos jugés sexistes misogynes en contexte médiatique
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In: https://tel.archives-ouvertes.fr/tel-03252459 ; Linguistique. Université Paul Valéry - Montpellier III, 2019. Français. ⟨NNT : 2019MON30112⟩ (2019)
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Le parler mixte népali-anglais : quelques éléments d'analyse descriptive à partir d'un corpus médiatique
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In: ISSN: 2617-0574 ; Interplay : A journal of Languages, Linguistics and Literature ; https://hal-normandie-univ.archives-ouvertes.fr/hal-02369127 ; Interplay : A journal of Languages, Linguistics and Literature, Department of Foreign Languages and Literature, Tunghai University, Taichung, Taiwan, R.O.C, 2019, 5, pp.52 - 81 (2019)
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The 2016 presidential primaries in the United States: a quantitative and qualitative approach to media coverage
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In: ISSN: 0039-3274 ; Studia Neophilologica ; https://hal.archives-ouvertes.fr/hal-01373150 ; Studia Neophilologica, Taylor & Francis (Routledge): SSH Titles, 2019 (2019)
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Detection and analysis of drug non-adherence in social media ; Détection et analyse de la non-adhérence médicamenteuse dans les réseaux sociaux
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In: https://tel.archives-ouvertes.fr/tel-02478927 ; Linguistique. Université de Lille, 2019. Français. ⟨NNT : 2019LILUH026⟩ (2019)
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Perception of media interpreting quality ; Perception de la qualité de l'interprétation dans les médias
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In: https://tel.archives-ouvertes.fr/tel-02864887 ; Linguistique. Université de la Sorbonne nouvelle - Paris III, 2019. Français. ⟨NNT : 2019PA030001⟩ (2019)
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Literature and press : a study of comprehension of texts (in Lebanese context) ; Littérature et presse : une étude de compréhension des textes (en contexte libanais)
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In: https://tel.archives-ouvertes.fr/tel-02448901 ; Linguistique. COMUE Université Côte d'Azur (2015 - 2019), 2019. Français. ⟨NNT : 2019AZUR2019⟩ (2019)
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Emphasis and expressivity in the speech of Nepali-English bilinguals ; Emphase et expressivité dans les échanges conversationnels bilingues népali-anglais
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In: ISSN: 2545-398X ; EISSN: 2545-3998 ; Palimpsest ; https://hal-normandie-univ.archives-ouvertes.fr/hal-02369157 ; Palimpsest, Faculty of Philology in Stip (2016-), 2019, 4 (7), pp.35-45 (2019)
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Willkommenskultur: A Computational and Socio-linguistic Study of Modern German Discourse on Migrant Populations
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In: Hartnett, Sabina. (2019). Willkommenskultur: A Computational and Socio-linguistic Study of Modern German Discourse on Migrant Populations. Transit, 12(1). Retrieved from: http://www.escholarship.org/uc/item/1x84x67r (2019)
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/pol/itically Incorrect: Ideologies of Race, Anti-Semitism, Gender and Sexuality in the Everyday Linguistic Co-production of Transgression
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In: Wilson, Wesley Troy. (2019). /pol/itically Incorrect: Ideologies of Race, Anti-Semitism, Gender and Sexuality in the Everyday Linguistic Co-production of Transgression. UCLA: Anthropology 0063. Retrieved from: http://www.escholarship.org/uc/item/3941s53n (2019)
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Multilingual and Multitarget Hate Speech Detection in Tweets
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In: Actes de la Conférence sur le Traitement Automatique des Langues Naturelles (TALN) PFIA 2019. Volume II : Articles courts ; Conférence sur le Traitement Automatique des Langues Naturelles (TALN - PFIA 2019) ; https://hal.archives-ouvertes.fr/hal-02567777 ; Conférence sur le Traitement Automatique des Langues Naturelles (TALN - PFIA 2019), Jul 2019, Toulouse, France. pp.351-360 ; https://www.aclweb.org/anthology/2019.jeptalnrecital-court.21/ (2019)
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Overwhelmed by Negative Emotions? Maybe You Are Being Cyber-bullied!
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In: Symposium On Applied Computing ; SAC 2019 - The 34th ACM/SIGAPP Symposium On Applied Computing ; https://hal.archives-ouvertes.fr/hal-02020829 ; SAC 2019 - The 34th ACM/SIGAPP Symposium On Applied Computing, Apr 2019, Limassol, Cyprus. ⟨10.1145/3297280.3297573⟩ (2019)
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Abstract:
International audience ; With the increasing number of interactions, social media users have been vulnerable to intentional aggressive acts and cyberbullying instances. In this paper, first, we carry out a message-level cyber-bullying annotation on an Instagram dataset. Second, we use the correlations on the Instagram dataset annotated with emotion, sentiment and bullying labels. Third, we build a message-level emotion classifier automatically predicting emotion labels for each comment in the Vine bullying dataset. Fourth, we build a session-based bullying classifier with the use of n-grams, emotion, sentiment and concept-level features. For both emotion and bullying classifiers, we use Linear Support Vector Classification. Our results show that "anger" and "negative" labels have a positive correlation with the presence of bullying. Concept-level features, emotion and sentiment features in different levels contribute to the bullying classifier, especially to the bullying class. Our best performing bullying classi-fier with n-grams and concept-level features (e.g., polarity, averaged polarity intensity, moodtags and semantics features) reaches to an F1-score of 0.65 for bullying class and a macro average F1-score of 0.7520.
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Keyword:
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; [INFO]Computer Science [cs]; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; [SHS]Humanities and Social Sciences; CCS CONCEPTS • Computing methodologies → Natural language processing; Cyberbullying detection; Emotion classification; Sentiment analysis; Social media
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URL: https://hal.archives-ouvertes.fr/hal-02020829/file/ACM_SigConf_SAC2019_1_1.pdf https://hal.archives-ouvertes.fr/hal-02020829/document https://hal.archives-ouvertes.fr/hal-02020829 https://doi.org/10.1145/3297280.3297573
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