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Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators' Disagreement ...
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FrameNet-like Annotation of Olfactory Information in Texts ...
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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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Abstract:
In order to study online hate speech, the availability of datasets containing the linguistic phenomena of interest are of crucial importance. However, when it comes to specific target groups, for example teenagers, collecting such data may be problematic due to issues with consent and privacy restrictions. Furthermore, while text-only datasets of this kind have been widely used, limitations set by image-based social media platforms like Instagram make it difficult for researchers to experiment with multimodal hate speech data. We therefore developed CREENDER, an annotation tool that has been used in school classes to create a multimodal dataset of images and abusive comments, which we make freely available under Apache 2.0 license. The corpus, with Italian comments, has been analysed from different perspectives, to investigate whether the subject of the images plays a role in triggering a comment. We find that users judge the same images in different ways, although the presence of a person in the picture ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2005.02235
https://dx.doi.org/10.48550/arxiv.2005.02235
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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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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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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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Topic-based agreement and disagreement in US electoral manifestos
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Fifty years of European history through the Lens of Computational Linguistics: the De Gasperi Project
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