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Automatic Expansion of Lexicons for Multilingual Misogyny Detection [chapter]

Simona Frenda, Bilal Ghanem, Estefanía Guzmán-Falcón, Manuel Montes-y-Gómez, Luis Villaseñor-Pineda
2018 EVALITA Evaluation of NLP and Speech Tools for Italian  
Acknowledgments The work of Simona Frenda was partially funded by the Spanish research project SomEMBED TIN2015-71147-C2-1-P (MINECO/FEDER).  ...  Considering the encouraging results obtained for Spanish and English in the precedent edition of AMI, in the EVALITA framework we tested the robustness of a similar approach based on topic and stylistic  ...  Proposed Approaches The AMI shared task proposed at EVALITA 2018 aims to detect misogyny in English and Italian collections of tweets.  ... 
doi:10.4000/books.aaccademia.4680 fatcat:javvsus63basffhfrncjfiohkm

GL at SemEval-2019 Task 5: Identifying hateful tweets with a deep learning approach

Gretel Liz De la Peña
2019 Proceedings of the 13th International Workshop on Semantic Evaluation  
We use an approach based on an Attention-based Long Short-Term Memory Recurrent Neural Network.  ...  This paper describes the system we developed for SemEval 2019 on Multilingual detection of hate speech against immigrants and women in Twitter (HatEval -Task 5).  ...  In this way, a linguistic characteristic is added to R according to the number of words in the tweet that appear in the dictionary.  ... 
doi:10.18653/v1/s19-2073 dblp:conf/semeval/Pena19 fatcat:y2ihzbwgufhtzj65awbu7wz6hy

Automatic classification of sexism in social networks: an empirical study on Twitter data

Francisco Rodriguez-Sanchez, Jorge Carrillo-de-Albornoz, Laura Plaza
2020 IEEE Access  
Our results show that sexism is frequently found in many forms in social networks, that it includes a wide range of behaviours, and that it is possible to detect them using deep learning approaches.  ...  To this end, we have developed and released the first dataset of sexist expressions and attitudes in Twitter in Spanish (MeTwo) and investigate the feasibility of using machine learning techniques (both  ...  Regarding feature extraction, we compared methods based on traditional tf-idf features to word embeddings approaches.  ... 
doi:10.1109/access.2020.3042604 fatcat:yaucfvtnrjfzjlnmn7rzzvgta4

Do Linguistic Features Help Deep Learning? The Case of Aggressiveness in Mexican Tweets

Simona Frenda, Somnath Banerjee, Paolo Rosso, Viviana Patti
2020 Journal of Computacion y Sistemas  
Considering the complexity and the importance of this issue, this paper presents an approach that combines the deep learning framework with linguistic features for the recognition of aggressiveness in  ...  This approach has been evaluated relying on a collection of tweets released by the organizers of the shared task about aggressiveness detection in the context of the Ibereval 2018 evaluation campaign.  ...  Acknowledgment The work of Simona Frenda and Paolo Rosso was partially funded by the Spanish MINECO under the research project SomEMBED (TIN2015-71147-C2-1-P).  ... 
doi:10.13053/cys-24-2-3398 fatcat:suxecnzyefhkvkb2ove22lflei

SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter

Valerio Basile, Cristina Bosco, Elisabetta Fersini, Debora Nozza, Viviana Patti, Francisco Manuel Rangel Pardo, Paolo Rosso, Manuela Sanguinetti
2019 Proceedings of the 13th International Workshop on Semantic Evaluation  
The task is organized in two related classification subtasks: a main binary subtask for detecting the presence of hate speech, and a finer-grained one devoted to identifying further features in hateful  ...  The paper describes the organization of the SemEval 2019 Task 5 about the detection of hate speech against immigrants and women in Spanish and English messages extracted from Twitter.  ...  Consequently, external resources such as pre-trained Word Embeddings on tweets have been widely adopted as input features.  ... 
doi:10.18653/v1/s19-2007 dblp:conf/semeval/BasileBFNPPRS19 fatcat:n7ztubkknvaxzktcbw5f26lsaa

Online Hate Speech against Women: Automatic Identification of Misogyny and Sexism on Twitter

Simona Frenda, Bilal Ghanem, Manuel Montes-y-Gómez, Paolo Rosso, David Pinto, Vivek Singh
2019 Journal of Intelligent & Fuzzy Systems  
In this difficult context, this paper presents an approach that is able to detect the two sides of patriarchal behavior, misogyny and sexism, analyzing three collections of English tweets, and obtaining  ...  Patriarchal behavior, such as other social habits, has been transferred online, appearing as misogynistic and sexist comments, posts or tweets.  ...  Acknowledgments The work of Simona Frenda and Paolo Rosso was partially funded by the Spanish MINECO under the research project SomEMBED (TIN2015-71147-C2-1-P).  ... 
doi:10.3233/jifs-179023 fatcat:qa32vaolcvdzjph7z7adq7fpme

Introduction to the Special Section on Computational Modeling and Understanding of Emotions in Conflictual Social Interactions

Rossana Damiano, Viviana Patti, Chloé Clavel, Paolo Rosso
2020 ACM Transactions on Internet Technology  
that copies bear this notice and the full citation on the first page.  ...  ACKNOWLEDGMENTS We would like to thank Editor in Chief Liu Ling and the editorial staff of ACM and ACM TOIT for their support in difficult times, and all authors for their valuable contributions.  ...  The article "Detecting Misogyny and Xenophobia in Spanish Tweets: Create Appropriate Language Resources for Hate Speech Detection in Spanish" [14] addresses the detection of hate speech in Spanish tweets  ... 
doi:10.1145/3392334 fatcat:swor5tggcnh3ndo3pe7mfjl7iq

Cross-domain and Cross-lingual Abusive Language Detection: A Hybrid Approach with Deep Learning and a Multilingual Lexicon

Endang Wahyu Pamungkas, Viviana Patti
2019 Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop  
A hybrid approach with deep learning and a multilingual lexicon to cross-domain and cross-lingual detection of abusive content is proposed and compared with other simpler models.  ...  However, abusive language behaviour is multifaceted and available datasets are featured by different topical focuses.  ...  Pamungkas and Viviana Patti was partially funded by Progetto di Ateneo/CSP 2016 (Immigrants, Hate and Prejudice in Social Media, S1618 L2 BOSC 01).  ... 
doi:10.18653/v1/p19-2051 dblp:conf/acl/PamungkasP19 fatcat:vqpvsyz7sbaflcytgqasnpnvqy

A Language Model for Misogyny Detection in Latin American Spanish Driven by Multisource Feature Extraction and Transformers

Edwin Aldana-Bobadilla, Alejandro Molina-Villegas, Yuridia Montelongo-Padilla, Ivan Lopez-Arevalo, Oscar S. Sordia
2021 Applied Sciences  
This research contributes to the development of models for the automatic detection of misogynistic texts in Latin American Spanish and contributes to the design of data augmentation methodologies since  ...  words, jokes, parodies, and other expressions.  ...  Data Availability Statement: Publicly available datasets were analyzed in this study. This data can be found here: (accessed on 4 November 2021).  ... 
doi:10.3390/app112110467 fatcat:hrsqz2oe5rbhhnonbjxgtz5eia

Overview of the Evalita 2018 Task on Automatic Misogyny Identification (AMI) [chapter]

Elisabetta Fersini, Debora Nozza, Paolo Rosso
2018 EVALITA Evaluation of NLP and Speech Tools for Italian  
The AMI challenge, based on both Italian and English tweets, is distinguished into two subtasks, i.e.  ...  Subtask A on misogyny identification and Subtask B about misogynistic behaviour categorization and target classification.  ...  We thank Maria Anzovino for her initial help in collecting the tweets subsequently used for the labelling phase and the final creation of the Italian and English corpora used for the AMI shared task.  ... 
doi:10.4000/books.aaccademia.4497 fatcat:f3bitvdcj5fu7klzpbmrv6ku3q

Emotionally Informed Hate Speech Detection: A Multi-target Perspective

Patricia Chiril, Endang Wahyu Pamungkas, Farah Benamara, Véronique Moriceau, Viviana Patti
2021 Cognitive Computation  
approach outperforms a single-task model when detecting both the hatefulness of a tweet and its topical focus in the context of a multi-label classification approach; and (3) the models incorporating  ...  EmoSenticNet emotions, the first level emotions of SenticNet, a blend of SenticNet and EmoSenticNet emotions or affective features based on Hurtlex, obtained the best results.  ...  Pamungkas and Viviana Patti is partially funded by Progetto di Ateneo/CSP 2016 (Immigrants, Hate and Prejudice in Social Media, S1618.L2.BOSC.01) and by the project "Be Positive!"  ... 
doi:10.1007/s12559-021-09862-5 fatcat:742czn3qvnep5gt6hkaoccz75m

Towards Interpretable Multilingual Detection of Hate Speech against Immigrants and Women in Twitter at SemEval-2019 Task 5 [article]

Alvi Md Ishmam
2020 arXiv   pre-print
his paper describes our techniques to detect hate speech against women and immigrants on Twitter in multilingual contexts, particularly in English and Spanish.  ...  features.  ...  As a result, the classifier performance improved by 18% based on syntactic, semantic, and context-based features. IX.  ... 
arXiv:2011.13238v1 fatcat:tpm3iwxntbcbzjc6ohfeagegwy

A Multi-task Learning Approach to Hate Speech Detection Leveraging Sentiment Analysis

Flor Miriam Plaza-Del-Arco, M. Dolores Molina-Gonzalez, L. Alfonso Urena-Lopez, Maria Teresa Martin-Valdivia
2021 IEEE Access  
In [21] authors developed a system for Twitter HS text identification based on two CNNs and feature embeddings including one-hot encoded character n-gram vectors and word embeddings, and they reported  ...  [33] proposed a system based on linguistic features, semantic similarity with a domain-oriented lexicon, sentiments (using the sentiment vocabulary weighted by the TF-IDF measure), word embeddings,  ...  She is full professor in the Department of Computer Science at University of Jaén (Spain).  ... 
doi:10.1109/access.2021.3103697 fatcat:argscoqcivgmdflfsf5erlnugy

Deep Neural Network for Gender-Based Violence Detection on Twitter Messages

Carlos M. Castorena, Itzel M. Abundez, Roberto Alejo, Everardo E. Granda-Gutiérrez, Eréndira Rendón, Octavio Villegas
2021 Mathematics  
in text and we think that these words do not contribute to discriminatory messages on Twitter).  ...  In this work, a deep learning neural network application to identify gender-based violence on Twitter messages is presented.  ...  Techniques like N-grams, linguistic, syntactic and embedding were used in order to build the feature space of the training data set.  ... 
doi:10.3390/math9080807 fatcat:scq37puxt5bzlai5jagayvm4s4

Exploring Misogyny across the Manosphere in Reddit

Tracie Farrell, Miriam Fernandez, Jakub Novotny, Harith Alani
2019 Proceedings of the 10th ACM Conference on Web Science - WebSci '19  
Serious accusations have been levied against it for its role in encouraging misogyny and violent threats towards women online, as well as for potentially radicalising lonely or disenfranchised men.  ...  Our results shows increasing patterns on misogynistic content and users as well as violent attitudes, corroborating existing theories of feminist studies that the amount of misogyny, hostility and violence  ...  Based on a sample of 138,662 tweets they studied the over time evolution of this word, and differentiated between casual and offensive misogyny.  ... 
doi:10.1145/3292522.3326045 dblp:conf/websci/FreyFNA19 fatcat:lfppjvaao5c2fcqe3mcsbwmvwu
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