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Dependency Syntax in the Automatic Detection of Irony and Stance ; Sintaxis de dependencias en la detección automática de ironía y posicionamiento
Cignarella, Alessandra Teresa. - : Sociedad Española para el Procesamiento del Lenguaje Natural, 2022
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2
Enjeux liés à la détection de l’ironie
In: Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 2 : 23e REncontres jeunes Chercheurs en Informatique pour le TAL (RECITAL) ; Traitement Automatique des Langues Naturelles ; https://hal.archives-ouvertes.fr/hal-03265905 ; Traitement Automatique des Langues Naturelles, 2021, Lille, France. pp.55-66 (2021)
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3
Dependency Syntax in the Automatic Detection of Irony and Stance
Cignarella, Alessandra Teresa. - : Universitat Politècnica de València, 2021
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4
Contributions to the Computational Treatment of Non-literal Language
Rohanian, Omid. - : University of Wolverhampton, 2020
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5
Irony Detection in Twitter with Imbalanced Class Distributions
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Transformer based contextualization of pre-trained word embeddings for irony detection in Twitter
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7
RGCL at IDAT: deep learning models for irony detection in Arabic language
In: 2517 ; 416 ; 425 (2019)
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8
Computational models for irony detection in three Spanish variants
Frenda S.; Patti V.. - : CEUR-WS, 2019. : country:ESP, 2019. : place:Bilbao, 2019
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9
Effectiveness of data-driven induction of semantic spaces and traditional classifiers for sarcasm detection
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10
IDAT@FIRE2019: Overview of the Track on Irony Detection in Arabic Tweets
Abstract: [EN] This overview paper describes the first shared task on irony detection for the Arabic language. The task consists of a binary classification of tweets as ironic or not using a dataset composed of 5,030 Arabic tweets about different political issues and events related to the Middle East and the Maghreb. Tweets in our dataset are written in Modern Standard Arabic but also in different Arabic language varieties including Egypt, Gulf, Levantine and Maghrebi dialects. Eighteen teams registered to the task among which ten submitted their runs. The methods of participants ranged from feature-based to neural networks using either classical machine learning techniques or ensemble methods. The best performing system achieved F-score value of 0.844, showing that classical feature-based models outperform the neural ones. ; This publication was made possible by NPRP grant 9-175-1-033 from the Qatar National Research Fund (a member of Qatar Foundation). The findings achieved herein are solely the responsibility of the last author. The work of Paolo Rosso was also partially funded by Generalitat Valenciana under grant PROMETEO/2019/121. ; Ghanem, B.; Karoui, J.; Benamara, F.; Moriceau, V.; Rosso, P. (2019). IDAT@FIRE2019: Overview of the Track on Irony Detection in Arabic Tweets. CEUR-WS.org. 380-390. http://hdl.handle.net/10251/180744 ; S ; 380 ; 390
Keyword: Arabic language; Irony detection; LENGUAJES Y SISTEMAS INFORMATICOS; Social media
URL: http://hdl.handle.net/10251/180744
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11
WLV at SemEval-2018 task 3: Dissecting tweets in search of irony
Rohanian, Omid; Taslimipoor, Shiva; Evans, Richard. - : Association for Computational Linguistics, 2018
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12
A survey on author profiling, deception, and irony detection for the Arabic language
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13
Sentiment Polarity Classification at EVALITA: Lessons Learned and Open Challenges
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14
A Knowledge-Based Weighted KNN for Detecting Irony in Twitter
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15
A survey on author profiling, deception, and irony detection for the Arabic language
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SOUKHRIA: Towards an Irony Detection System for Arabic in Social Media
In: 3rd International Conference on Arabic Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-01686504 ; 3rd International Conference on Arabic Computational Linguistics, Nov 2017, Dubaï, United Arab Emirates. pp.161 - 168, ⟨10.1016/j.procs.2017.10.105⟩ (2017)
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17
Ironic gestures and tones in twitter
Frenda, Simona. - : CEUR-WS, 2017. : country:DEU, 2017. : place:Aachen, 2017
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18
Irony and Sarcasm Detection in Twitter: The Role of Affective Content
Hernández Farias, Delia Irazu. - : Universitat Politècnica de València, 2017
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19
Special Session on Emotion and Sentiment in Intelligent Systems and Big Social Data Analysis (SentISData 2016)
In: 3rd IEEE International Conference on Data Science and Advanced Analytics (DSAA 2016) ; https://hal.archives-ouvertes.fr/hal-03176429 ; Benamara, Farah; Bosco, Cristina; Fersini, Elisabetta; Patti, Viviana; Viviancos, Emilio. 3rd IEEE International Conference on Data Science and Advanced Analytics (DSAA 2016), Oct 2016, Montréal, Canada. 2016 ; https://sites.ualberta.ca/~dsaa16/specialsessions.html (2016)
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20
Character and Word Baselines for Irony Detection in Spanish Short Texts ; Sistemas de detección de ironía basados en palabras y caracteres para textos cortos en español
Jasso, Gabriela; Meza Ruiz, Iván Vladimir. - : Sociedad Española para el Procesamiento del Lenguaje Natural, 2016
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