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Dependency Syntax in the Automatic Detection of Irony and Stance
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Treebanking user-generated content: a proposal for a unified representation in universal dependencies
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In: Sanguinetti, Manuela orcid:0000-0002-0147-2208 , Bosco, Cristina, Cassidy, Lauren, Çetinoglu, Özlem, Cignarella, Alessandra Teresa orcid:0000-0002-4409-6679 , Lynn, Teresa, Rehbein, Ines, Ruppenhofer, Josef, Seddah, Djamé and Zeldes, Amir orcid:0000-0001-8016-6753 (2020) Treebanking user-generated content: a proposal for a unified representation in universal dependencies. In: 12th Language Resources and Evaluation Conference. (LREC 2020), 11-16 May 2020, Marseille, France. (2020)
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Treebanking user-generated content: a proposal for a unified representation in universal dependencies
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In: Sanguinetti, Manuela orcid:0000-0002-0147-2208 , Bosco, Cristina, Cassidy, Lauren, Çetinoglu, Özlem, Cignarella, Alessandra Teresa orcid:0000-0002-4409-6679 , Lynn, Teresa, Rehbein, Ines, Ruppenhofer, Josef, Seddah, Djamé and Zeldes, Amir orcid:0000-0001-8016-6753 (2020) Treebanking user-generated content: a proposal for a unified representation in universal dependencies. In: 12th Language Resources and Evaluation Conference. (LREC 2020), 11-16 May 2020, Marseille, France. (Virtual). (2020)
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Multilingual Irony Detection with Dependency Syntax and Neural Models
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In: Proceedings of the 28th International Conference on Computational Linguistics ; 28th International Conference on Computational Linguistics (COLING 2020) ; https://hal.archives-ouvertes.fr/hal-03102480 ; 28th International Conference on Computational Linguistics (COLING 2020), Dec 2020, Barcelona (Online), Spain. pp.1346-1358 ; https://www.aclweb.org/anthology/2020.coling-main.116/ (2020)
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Abstract:
International audience ; This paper presents an in-depth investigation of the effectiveness of dependency-based syntactic features on the irony detection task in a multilingual perspective (English, Spanish, French and Italian). It focuses on the contribution from syntactic knowledge, exploiting linguistic resources where syntax is annotated according to the Universal Dependencies scheme. Three distinct experimental settings are provided. In the first, a variety of syntactic dependency-based features combined with classical machine learning classifiers are explored. In the second scenario, two well-known types of word embeddings are trained on parsed data and tested against gold standard datasets. In the third setting, dependency-based syntactic features are combined into the Multilingual BERT architecture. The results suggest that fine-grained dependency-based syntactic information is informative for the detection of irony.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing
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URL: https://hal.archives-ouvertes.fr/hal-03102480
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Multilingual Irony Detection with Dependency Syntax and Neural Models ...
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Treebanking User-Generated Content: a UD Based Overview of Guidelines, Corpora and Unified Recommendations ...
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Multilingual Irony Detection with Dependency Syntax and Neural Models ...
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EVALITA4ELG: Italian Benchmark Linguistic Resources, NLP Services and Tools for the ELG Platform
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“Contro L’Odio”: A Platform for Detecting, Monitoring and Visualizing Hate Speech against Immigrants in Italian Social Media
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Treebanking user-generated content: A proposal for a unified representation in universal dependencies
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Multilingual Stance Detection in Social Media Political Debates
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