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Monolingual and Cross-Lingual Acceptability Judgments with the Italian CoLA corpus ...
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Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators' Disagreement ...
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Fine-Grained Fairness Analysis of Abusive Language Detection Systems with CheckList ...
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FrameNet-like Annotation of Olfactory Information in Texts ...
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Monolingual and Cross-Lingual Acceptability Judgments with the Italian CoLA corpus ...
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A Smell is Worth a Thousand Words: Olfactory Information Extraction and Semantic Processing in a Multilingual Perspective (Invited Talk) ...
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Tonelli, Sara. - : Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021
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Hybrid Emoji-Based Masked Language Models for Zero-Shot Abusive Language Detection
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In: EMNLP 2020 - Conference on Empirical Methods in Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-02972203 ; EMNLP 2020 - Conference on Empirical Methods in Natural Language Processing, Nov 2020, Virtual, France (2020)
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A Multilingual Evaluation for Online Hate Speech Detection
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In: ISSN: 1533-5399 ; ACM Transactions on Internet Technology ; https://hal.archives-ouvertes.fr/hal-02972184 ; ACM Transactions on Internet Technology, Association for Computing Machinery, 2020, 20 (2), pp.1-22. ⟨10.1145/3377323⟩ (2020)
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Creating a Multimodal Dataset of Images and Text to Study Abusive Language ...
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Cross-Platform Evaluation for Italian Hate Speech Detection
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In: CLiC-it 2019 - 6th Annual Conference of the Italian Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02381152 ; CLiC-it 2019 - 6th Annual Conference of the Italian Association for Computational Linguistics, Nov 2019, Bari, Italy (2019)
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Enhancing statistical machine translation with bilingual terminology in a CAT environment
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The impact of phrases on Italian lexical simplification ...
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The impact of phrases on Italian lexical simplification ...
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Never Retreat, Never Retract: Argumentation Analysis for Political Speeches
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In: Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence ; AAAI 2018 - 32nd AAAI Conference on Artificial Intelligence ; https://hal.archives-ouvertes.fr/hal-01876442 ; AAAI 2018 - 32nd AAAI Conference on Artificial Intelligence, Feb 2018, New Orleans, United States. pp.4889-4896 ; https://aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16393 (2018)
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Abstract:
International audience ; In this work, we apply argumentation mining techniques, in particular relation prediction, to study political speeches in monological form, where there is no direct interaction between opponents. We argue that this kind of technique can effectively support researchers in history, social and political sciences, which must deal with an increasing amount of data in digital form and need ways to automatically extract and analyse argumentation patterns. We test and discuss our approach based on the analysis of documents issued by R. Nixon and J. F. Kennedy during 1960 presidential campaign. We rely on a supervised classifier to predict argument relations (i.e., support and attack), obtaining an accuracy of 0.72 on a dataset of 1,462 argument pairs. The application of argument mining to such data allows not only to highlight the main points of agreement and disagreement between the candidates' arguments over the campaign issues such as Cuba, disarmament and health-care, but also an in-depth argumentative analysis of the respective viewpoints on these topics.
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Keyword:
[SCCO.COMP]Cognitive science/Computer science; [SCCO.LING]Cognitive science/Linguistics; Argument mining; Political speeches; Support and attack classification
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URL: https://hal.archives-ouvertes.fr/hal-01876442/file/16393-76780-1-PB%281%29.pdf https://hal.archives-ouvertes.fr/hal-01876442 https://hal.archives-ouvertes.fr/hal-01876442/document
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InriaFBK at Germeval 2018: Identifying Offensive Tweets Using Recurrent Neural Networks
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In: http://hw.oeaw.ac.at/8435-5 (2018)
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