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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5...8 Hits 1 – 20 of 148 1 Detecting early signs of depression in the conversational domain: The role of transfer learning in low-resource scenarios ... Lorenc, Petr; Uban, Ana-Sabina; Rosso, Paolo. - : arXiv, 2022 BASE Show details 2 Predicting subjective well-being in a high-risk sample of Russian mental health app users Panicheva, Polina; Mararitsa, Larisa; Sorokin, Semen... In: EPJ Data Sci (2022) BASE Show details 3 LIMSI_UPV at SemEval-2020 Task 9: Recurrent Convolutional Neural Network for Code-mixed Sentiment Analysis Banerjee, Somnath; Ghannay, Sahar; Rosset, Sophie... In: https://hal.archives-ouvertes.fr/hal-03294371 ; 2021 (2021) BASE Show details 4 UPV at CheckThat! 2021: Mitigating Cultural Differences for Identifying Multilingual Check-worthy Claims ... Schlicht, Ipek Baris; de Paula, Angel Felipe Magnossão; Rosso, Paolo. - : arXiv, 2021 BASE Show details 5 Categorizing Misogynistic Behaviours in Italian, English and Spanish Tweets ; Categorización de comportamientos misóginos en tweets en italiano, inglés y español Lazzardi, Silvia; Patti, Viviana; Rosso, Paolo. - : Sociedad Española para el Procesamiento del Lenguaje Natural, 2021 Abstract: Misogyny is a multifaceted phenomenon and can be linguistically manifested in numerous ways. The evaluation campaigns of EVALITA and IberEval in 2018 proposed a shared task of Automatic Misogyny Identification (AMI) based on Italian, English and Spanish tweets. Since the participating teams' results were pretty low in the misogynistic behaviour categorization, the aim of this study is to investigate the possible causes. We measured the overlap and the homogeneity of the clusters by varying the number of categories. This experiment showed that the clusters overlap. Finally, we tested several machine learning models both using the original data sets and merging together some categories according to their overlap, obtaining an increase in terms of macro F1. ; La misoginia es un fenómeno con múltiples facetas y puede manifestarse lingüísticamente de muchas formas. Las campañas de evaluación de EVALITA e IberEval en 2018 propusieron una tarea compartida de Identificación Automática de Misoginia (AMI) basada en tweets en italiano, inglés y español. Dado que los resultados de los equipos participantes fueron bastante bajos en la categorización del comportamiento misógino, el objetivo de este estudio es investigar las posibles causas. Medimos el solape y la homogeneidad de los clústeres variando el número de categorías. Este experimento mostró que los grupos se solapan. Finalmente probamos varios modelos de aprendizaje automático utilizando los conjuntos de datos originales y fusionando algunas categorías de acuerdo con consideraciones basadas en medidas de similitud y las matrices de confusión de los modelos, obteniendo un aumento de la F1 macro. ; The work of S. Lazzardi was partially carried out at the Universitat Politècnica de València within the framework of the Erasmus+ program, Erasmus Traineeship 2018/19 funding. The work of P. Rosso was partially funded by the Spanish MICINN under the research project MISMIS-FAKEnHATE on Misinformation and Miscommunication in social media: FAKE news and HATE speech (PGC2018-096212-B-C31). The work of V. Patti was partially funded by the research projects “STudying European Racial Hoaxes and sterEOTYPES” (STERHEOTYPES, under the call “Challenges for Europe” of VolksWagen Stiftung and Compagnia di San Paolo) and “Be Positive!” (under the 2019 “Google.org Impact Challenge on Safety” call). Keyword: Automatic misogyny identification; Hate speech online; Identificación automática de misoginia; Lenguajes y Sistemas Informáticos; Mensajes de odio online URL: http://hdl.handle.net/10045/114226 https://doi.org/10.26342/2021-66-5 BASE Hide details 6 Masking and BERT-based Models for Stereotype Identification ; Modelos Basados en Enmascaramiento y en BERT para la Identificación de Estereotipos Sánchez-Junquera, Javier; Rosso, Paolo; Montes y Gómez, Manuel. - : Sociedad Española para el Procesamiento del Lenguaje Natural, 2021 BASE Show details 7 The impact of emotional signals on credibility assessment Giachanou, Anastasia; Rosso, Paolo; Crestani, Fabio In: J Assoc Inf Sci Technol (2021) BASE Show details 8 On the Detection of False Information: From Rumors to Fake News Ghanem, Bilal Hisham Hasan. - : Universitat Politècnica de València, 2021 BASE Show details 9 Dependency Syntax in the Automatic Detection of Irony and Stance Cignarella, Alessandra Teresa. - : Universitat Politècnica de València, 2021 BASE Show details 10 Fake opinion detection: how similar are crowdsourced datasets to real data? [<Journal>] Fornaciari, Tommaso [Verfasser]; Cagnina, Leticia [Verfasser]; Rosso, Paolo [Verfasser]. DNB Subject Category Language Show details 11 Multilingual Irony Detection with Dependency Syntax and Neural Models Signarella, Alessandra Teresa; Basile, Valerio; Sanguinetti, Manuela... 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) BASE Show details 12 Irony Detection in a Multilingual Context Ghanem, Bilal; Karoui, Jihen; Benamara, Farah... In: ECIR ; https://hal.archives-ouvertes.fr/hal-02889008 ; ECIR, Apr 2020, online, Portugal (2020) BASE Show details 13 Irony Detection in a Multilingual Context ... Ghanem, Bilal; Karoui, Jihen; Benamara, Farah. - : arXiv, 2020 BASE Show details 14 LIMSI_UPV at SemEval-2020 Task 9: Recurrent Convolutional Neural Network for Code-mixed Sentiment Analysis ... Banerjee, Somnath; Ghannay, Sahar; Rosset, Sophie. - : arXiv, 2020 BASE Show details 15 Classifier Combination Approach for Question Classification for Bengali Question Answering System ... Banerjee, Somnath; Naskar, Sudip Kumar; Rosso, Paolo. - : arXiv, 2020 BASE Show details 16 Multilingual Irony Detection with Dependency Syntax and Neural Models ... Cignarella, Alessandra Teresa; Basile, Valerio; Sanguinetti, Manuela. - : arXiv, 2020 BASE Show details 17 Multilingual Irony Detection with Dependency Syntax and Neural Models ... The 28th International Conference on Computational Linguistics 2020; Basile, Valerio; Benamara, Farah. - : Underline Science Inc., 2020 BASE Show details 18 Irony Detection in a Multilingual Context Ghanem, Bilal; Karoui, Jihen; Benamara, Farah. - 2020 BASE Show details 19 The Role of Personality and Linguistic Patterns in Discriminating Between Fake News Spreaders and Fact Checkers Giachanou, Anastasia; Ríssola, Esteban A.; Ghanem, Bilal... In: Natural Language Processing and Information Systems (2020) BASE Show details 20 Do Linguistic Features Help Deep Learning? The Case of Aggressiveness in Mexican Tweets Frenda, Simona; Banerjee, Somnath; Rosso, Paolo. - 2020 BASE Show details Page: 1 2 3 4 5...8

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