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Can Character-based Language Models Improve Downstream Task Performance in Low-Resource and Noisy Language Scenarios?
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In: Seventh Workshop on Noisy User-generated Text (W-NUT 2021, colocated with EMNLP 2021) ; https://hal.inria.fr/hal-03527328 ; Seventh Workshop on Noisy User-generated Text (W-NUT 2021, colocated with EMNLP 2021), Jan 2022, punta cana, Dominican Republic ; https://aclanthology.org/2021.wnut-1.47/ (2022)
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Cross-lingual few-shot hate speech and offensive language detection using meta learning
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In: ISSN: 2169-3536 ; EISSN: 2169-3536 ; IEEE Access ; https://hal.archives-ouvertes.fr/hal-03559484 ; IEEE Access, IEEE, 2022, 10, pp.14880-14896. ⟨10.1109/ACCESS.2022.3147588⟩ (2022)
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A comparative study of different features for efficient automatic hate speech detection
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In: IPrA 2021 - 17th International Pragmatics Conference ; https://hal.archives-ouvertes.fr/hal-03115781 ; IPrA 2021 - 17th International Pragmatics Conference, Jun 2021, Winterthur, Switzerland (2021)
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Multiword Expression Features for Automatic Hate Speech Detection
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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)
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Management support system and group planning in continuing education ; Système d’aide à la gestion et planification de groupe en formation continue
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In: https://hal.archives-ouvertes.fr/tel-03557025 ; Environnements Informatiques pour l'Apprentissage Humain. Université de Lille, CRIStAL UMR 9189, 2021. Français (2021)
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Dynamics of cascades on burstiness-controlled temporal networks
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In: ISSN: 2041-1723 ; EISSN: 2041-1723 ; Nature Communications ; https://hal.inria.fr/hal-03117999 ; Nature Communications, Nature Publishing Group, 2021, 12 (1), pp.1-9. ⟨10.1038/s41467-020-20398-4⟩ (2021)
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Hate speech and offensive language detection using transfer learning approaches ; Détection du discours de haine et du langage offensant utilisant des approches de Transfer Learning
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In: https://tel.archives-ouvertes.fr/tel-03276023 ; Document and Text Processing. Institut Polytechnique de Paris, 2021. English. ⟨NNT : 2021IPPAS007⟩ (2021)
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Dataset of coronavirus content from Instagram with an exploratory analysis
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In: ISSN: 2169-3536 ; EISSN: 2169-3536 ; IEEE Access ; https://hal.archives-ouvertes.fr/hal-03559489 ; IEEE Access, IEEE, 2021, 9, pp.157192-157202. ⟨10.1109/ACCESS.2021.3126552⟩ (2021)
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Application-Oriented Approach for Detecting Cyberaggression in Social Media
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In: International Conference on Applied Human Factors and Ergonomics ; https://hal.archives-ouvertes.fr/hal-02903422 ; International Conference on Applied Human Factors and Ergonomics, Jul 2020, San Diego, United States. pp.129-136, ⟨10.1007/978-3-030-51328-3_19⟩ ; https://link.springer.com/chapter/10.1007%2F978-3-030-51328-3_19 (2020)
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Capitalizing on a TREC Track to Build a Tweet Summarization Dataset
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In: CIRCLE 2020 ; Proceedings of the Joint Conference of the Information Retrieval Communities in Europe (CIRCLE 2020) ; Joint Conference of the Information Retrieval Communities in Europe (CIRCLE 2020) ; https://hal.archives-ouvertes.fr/hal-03095613 ; Joint Conference of the Information Retrieval Communities in Europe (CIRCLE 2020), Université de Toulouse, France, Jul 2020, Samatan, Gers, France. pp.1-9 ; http://ceur-ws.org/Vol-2621/CIRCLE20_20.pdf (2020)
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Représentations lexicales pour la détection non supervisée d'événements dans un flux de tweets : étude sur des corpus français et anglais
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In: Extraction et Gestion des connaissances, EGC 2020 ; https://hal-centralesupelec.archives-ouvertes.fr/hal-02432990 ; Extraction et Gestion des connaissances, EGC 2020, Jan 2020, Bruxelles, Belgique (2020)
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Abstract:
International audience ; In this work, we evaluate the performance of recent text embeddings for the automatic detection of events in a stream of tweets. We model this task as a dynamic clustering problem.Our experiments are conducted on a publicly available corpus of tweets in English and on a similar dataset in French annotated by our team. We show that recent techniques based on deep neural networks (ELMo, Universal Sentence Encoder, BERT, SBERT), although promising on many applications, are not very suitable for this task. We also experiment with different types of fine-tuning to improve these results on French data. Finally, we propose a detailed analysis of the results obtained, showing the superiority of tf-idf approaches for this task. ; Dans cet article, nous nous intéressons aux approches récentes de plongements lexicaux en vue de les appliquer à la détection automatique d'événements dans un flux de tweets. Nous modélisons cette tâche comme un problème de clustering dynamique. Nos expériences sont menées sur un corpus de tweets en anglais accessible publiquement ainsi que sur un jeu de données similaire en français annoté par notre équipe. Nous montrons que les techniques récentes fondées sur des réseaux de neurones profonds (ELMo, Universal Sentence Encoder, BERT, SBERT), bien que prometteuses sur de nombreuses applications , sont peu adaptées pour cette tâche, même sur le corpus en anglais. Nous expérimentons également différents types de fine-tuning afin d'améliorer les résultats de ces modèles sur les données en français. Nous proposons enfin une analyse fine des résultats obtenus montrant la supériorité des approches traditionnelles de type tf-idf pour ce type de tâche et de corpus.
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Keyword:
[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]; [INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing
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URL: https://hal-centralesupelec.archives-ouvertes.fr/hal-02432990/file/EGC_2020.pdf https://hal-centralesupelec.archives-ouvertes.fr/hal-02432990/document https://hal-centralesupelec.archives-ouvertes.fr/hal-02432990
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Temporal social network reconstruction using wireless proximity sensors: model selection and consequences
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In: ISSN: 2193-1127 ; EISSN: 2193-1127 ; EPJ Data Science ; https://hal.inria.fr/hal-03117988 ; EPJ Data Science, EDP Sciences, 2020, 9 (1), ⟨10.1140/epjds/s13688-020-00237-8⟩ (2020)
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Using Twitter Streams for Opinion Mining: a case study on Airport Noise
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In: ISSN: 1865-0929 ; Communications in Computer and Information Science ; https://hal.archives-ouvertes.fr/hal-03018998 ; Communications in Computer and Information Science, Springer Verlag, 2020, ⟨10.1007/978-3-030-44900-1_10⟩ (2020)
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Using Sentiment Analysis for Pseudo-Relevance Feedback in Social Book Search
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In: ICTIR '20: The 2020 ACM SIGIR International Conference on the Theory of Information Retrieval ; https://hal.archives-ouvertes.fr/hal-03124566 ; ICTIR '20: The 2020 ACM SIGIR International Conference on the Theory of Information Retrieval, Sep 2020, Stavanger, Norway. pp.29-32, ⟨10.1145/3409256.3409847⟩ ; https://ictir2020.org (2020)
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Computational detection of socioeconomic inequalities ; Détection computationnelle des inégalités socioéconomiques
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In: https://hal.archives-ouvertes.fr/tel-02459170 ; Artificial Intelligence [cs.AI]. Université de Lyon, 2020. English. ⟨NNT : 2020LYSEN001⟩ (2020)
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Joint embedding of structure and features via graph convolutional networks
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In: ISSN: 2364-8228 ; EISSN: 2364-8228 ; Applied Network Science ; https://hal.inria.fr/hal-02388402 ; Applied Network Science, Springer, 2020, 5 (1), ⟨10.1007/s41109-019-0237-x⟩ (2020)
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Information Adoption via Repeated or Diversified Social Influence on Twitter
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In: ASONAM 2020 - IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining ; https://hal.inria.fr/hal-03197971 ; ASONAM 2020 - IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Dec 2020, The Hague, Netherlands. pp.237-241, ⟨10.1109/ASONAM49781.2020.9381365⟩ (2020)
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Interpretable socioeconomic status inference from aerial imagery through urban patterns
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In: EISSN: 2522-5839 ; Nature Machine Intelligence ; https://hal.inria.fr/hal-03117994 ; Nature Machine Intelligence, Nature Research, 2020, 2 (11), pp.684-692. ⟨10.1038/s42256-020-00243-5⟩ (2020)
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Affective behavior modeling on social networks ; Modélisation des sentiments sur les réseaux sociaux
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In: https://tel.archives-ouvertes.fr/tel-03339755 ; Social and Information Networks [cs.SI]. Université Montpellier, 2020. English. ⟨NNT : 2020MONTS073⟩ (2020)
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Novel Version of PageRank, CheiRank and 2DRank for Wikipedia in Multilingual Network Using Social Impact
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In: BIS: International Conference on Business Information Systems ; https://hal.archives-ouvertes.fr/hal-03217697 ; Witold Abramowicz, Gary Klein. BIS: International Conference on Business Information Systems, Springer, pp.319-334, 2020, 23rd International Conference, BIS 2020, Colorado Springs, CO, USA, June 8–10, 2020, Proceedings, 978-3-030-53337-3. ⟨10.1007/978-3-030-53337-3_24⟩ (2020)
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