Misogyny Detection in Twitter: a Multilingual and Cross-Domain Study

[1]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[2]  Thorsten Joachims,et al.  Text Categorization with Support Vector Machines: Learning with Many Relevant Features , 1998, ECML.

[3]  S. Riddell.  Routledge International Encyclopedia of Women , 2001 .

[4]  Lorraine Code,et al.  Encyclopedia of Feminist Theories , 2002 .

[5]  S. Pinker.  The Stuff of Thought: Language as a Window into Human Nature , 2007 .

[6]  Hal Daumé,et al.  Frustratingly Easy Domain Adaptation , 2007, ACL.

[7]  E. Cambria,et al.  Do Not Feel The Trolls , 2010 .

[8]  Yoshua Bengio,et al.  Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.

[9]  Byron C. Wallace,et al.  Humans Require Context to Infer Ironic Intent (so Computers Probably do, too) , 2014, ACL.

[10]  Andrea Carnaghi,et al.  Social acceptability of sexist derogatory and sexist objectifying slurs across contexts , 2015 .

[11]  A. Flammini,et al.  Misogynistic Language on Twitter and Sexual Violence , 2015 .

[12]  Bailey Poland,et al.  Haters: Harassment, Abuse, and Violence Online , 2016 .

[13]  Paolo Rosso,et al.  Figurative messages and affect in Twitter: Differences between #irony, #sarcasm and #not , 2016, Knowl. Based Syst..

[14]  Dirk Hovy,et al.  Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter , 2016, NAACL.

[15]  Joel R. Tetreault,et al.  Abusive Language Detection in Online User Content , 2016, WWW.

[16]  Thanassis Tiropanis,et al.  The problem of identifying misogynist language on Twitter (and other online social spaces) , 2016, WebSci.

[17]  Samuel L. Smith,et al.  Offline bilingual word vectors, orthogonal transformations and the inverted softmax , 2017, ICLR.

[18]  Mike Thelwall,et al.  Sentiment Analysis Is a Big Suitcase , 2017, IEEE Intelligent Systems.

[19]  Radhika Mamidi,et al.  When does a compliment become sexist? Analysis and classification of ambivalent sexism using twitter data , 2017, NLP+CSS@ACL.

[20]  Erik Cambria,et al.  Deep Learning-Based Document Modeling for Personality Detection from Text , 2017, IEEE Intelligent Systems.

[21]  Nikos Pelekis,et al.  DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis , 2017, *SEMEVAL.

[22]  Tie-Yan Liu,et al.  LightGBM: A Highly Efficient Gradient Boosting Decision Tree , 2017, NIPS.

[23]  Vasudeva Varma,et al.  Deep Learning for Hate Speech Detection in Tweets , 2017, WWW.

[24]  Joachim Bingel,et al.  Sluice networks: Learning what to share between loosely related tasks , 2017, ArXiv.

[25]  Paolo Rosso,et al.  Overview of the Evalita 2018 Task on Automatic Misogyny Identification (AMI) , 2018, EVALITA@CLiC-it.

[26]  Jan Snajder,et al.  Cross-Domain Detection of Abusive Language Online , 2018, ALW.

[27]  Pascale Fung,et al.  Reducing Gender Bias in Abusive Language Detection , 2018, EMNLP.

[28]  John Cardiff,et al.  Classifying Misogynistic Tweets Using a Blended Model: The AMI Shared Task in IBEREVAL 2018 , 2018, IberEval@SEPLN.

[29]  Martine De Cock,et al.  Detecting Hate Speech Against Women in English Tweets , 2018, EVALITA@CLiC-it.

[30]  Erik Cambria,et al.  International Conference on Advances in Social Networks Analysis and Mining ( ASONAM ) Sounds of Silence Breakers : Exploring Sexual Violence on Twitter , 2018 .

[31]  Manuel Montes-y-Gómez,et al.  Exploration of Misogyny in Spanish and English Tweets , 2018, IberEval@SEPLN.

[32]  Animesh Mukherjee,et al.  Hateminers : Detecting Hate speech against Women , 2018, ArXiv.

[33]  Viviana Patti,et al.  14-ExLab@UniTo for AMI at IberEval2018: Exploiting Lexical Knowledge for Detecting Misogyny in English and Spanish Tweets , 2018, IberEval@SEPLN.

[34]  Guillaume Lample,et al.  Word Translation Without Parallel Data , 2017, ICLR.

[35]  Nerea Ezeiza,et al.  Automatic Misogyny Identification Using Neural Networks , 2018, IberEval@SEPLN.

[36]  Cristina Bosco,et al.  An Impossible Dialogue! Nominal Utterances and Populist Rhetoric in an Italian Twitter Corpus of Hate Speech against Immigrants , 2018, LREC.

[37]  Joachim Bingel,et al.  Bridging the Gaps: Multi Task Learning for Domain Transfer of Hate Speech Detection , 2018 .

[38]  Davide Buscaldi.  Tweetaneuse @ AMI EVALITA2018: Character-based Models for the Automatic Misogyny Identification Task (Short Paper) , 2018, EVALITA@CLiC-it.

[39]  Han Liu,et al.  Identification and Classification of Misogynous Tweets Using Multi-classifier Fusion , 2018, IberEval@SEPLN.

[40]  Michael Wiegand,et al.  Overview of the GermEval 2018 Shared Task on the Identification of Offensive Language , 2018 .

[41]  Georg Rehm,et al.  Towards the Automatic Classification of Offensive Language and Related Phenomena in German Tweets , 2018 .

[42]  Angelo Basile,et al.  CrotoneMilano for AMI at Evalita2018. A Performant, Cross-lingual Misogyny Detection System , 2018, EVALITA@CLiC-it.

[43]  Viviana Patti,et al.  Automatic Identification of Misogyny in English and Italian Tweets at EVALITA 2018 with a Multilingual Hate Lexicon , 2018, EVALITA@CLiC-it.

[44]  Helen Yannakoudakis,et al.  Author Profiling for Abuse Detection , 2018, COLING.

[45]  Malvina Nissim,et al.  Bleaching Text: Abstract Features for Cross-lingual Gender Prediction , 2018, ACL.

[46]  Erik Cambria,et al.  Multimodal Sentiment Analysis: Addressing Key Issues and Setting Up the Baselines , 2018, IEEE Intelligent Systems.

[47]  Amir Bakarov,et al.  Vector Space Models for Automatic Misogyny Identification (Short Paper) , 2018, EVALITA@CLiC-it.

[48]  Paolo Rosso,et al.  Automatic Identification and Classification of Misogynistic Language on Twitter , 2018, NLDB.

[49]  Paolo Rosso,et al.  Overview of the Task on Automatic Misogyny Identification at IberEval 2018 , 2018, IberEval@SEPLN.

[50]  Louise Richardson-Self,et al.  Woman‐Hating: On Misogyny, Sexism, and Hate Speech , 2018, Hypatia.

[51]  Mai ElSherief,et al.  Leveraging Intra-User and Inter-User Representation Learning for Automated Hate Speech Detection , 2018, NAACL.

[52]  Walter Daelemans,et al.  Automatic detection of cyberbullying in social media text , 2018, PloS one.

[53]  Shervin Malmasi,et al.  Challenges in discriminating profanity from hate speech , 2017, J. Exp. Theor. Artif. Intell..

[54]  Viviana Patti,et al.  Hurtlex: A Multilingual Lexicon of Words to Hurt , 2018, CLiC-it.

[55]  Kathleen McKeown,et al.  Predictive Embeddings for Hate Speech Detection on Twitter , 2018, ALW.

[56]  John Cardiff,et al.  Misogyny Detection and Classification in English Tweets: The Experience of the ITT Team , 2018, EVALITA@CLiC-it.

[57]  Jose Sebastián Canós.  Misogyny Identification Through SVM at IberEval 2018 , 2018, IberEval@SEPLN.

[58]  Luis Villaseñor Pineda,et al.  Automatic Expansion of Lexicons for Multilingual Misogyny Detection , 2018, EVALITA@CLiC-it.

[59]  Viviana Patti,et al.  Stance Classification for Rumour Analysis in Twitter: Exploiting Affective Information and Conversation Structure , 2018, CIKM Workshops.

[60]  Björn Gambäck,et al.  The Effects of User Features on Twitter Hate Speech Detection , 2018, ALW.

[61]  Victor Nina-Alcocer,et al.  AMI at IberEval2018 Automatic Misogyny Identification in Spanish and English Tweets , 2018, IberEval@SEPLN.

[62]  Preslav Nakov,et al.  Predicting the Type and Target of Offensive Posts in Social Media , 2019, NAACL.

[63]  Holger Schwenk,et al.  Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond , 2018, Transactions of the Association for Computational Linguistics.

[64]  Marco Guerini,et al.  CONAN - COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speech , 2019, ACL.

[65]  Sima Sharifirad,et al.  Learning and Understanding Different Categories of Sexism Using Convolutional Neural Network’s Filters , 2019, WNLP@ACL.

[66]  Yangqiu Song,et al.  Multilingual and Multi-Aspect Hate Speech Analysis , 2019, EMNLP.

[67]  Erik Cambria,et al.  Sentiment and Sarcasm Classification With Multitask Learning , 2019, IEEE Intelligent Systems.

[68]  Endang Wahyu Pamungkas,et al.  Cross-domain and Cross-lingual Abusive Language Detection: A Hybrid Approach with Deep Learning and a Multilingual Lexicon , 2019, ACL.

[69]  Michael Wiegand,et al.  Detection of Abusive Language: the Problem of Biased Datasets , 2019, NAACL.

[70]  Ingmar Weber,et al.  Racial Bias in Hate Speech and Abusive Language Detection Datasets , 2019, Proceedings of the Third Workshop on Abusive Language Online.

[71]  Paolo Rosso,et al.  SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter , 2019, *SEMEVAL.

[72]  Paolo Rosso,et al.  Online Hate Speech against Women: Automatic Identification of Misogyny and Sexism on Twitter , 2019, J. Intell. Fuzzy Syst..

[73]  Noel Crespi,et al.  A BERT-Based Transfer Learning Approach for Hate Speech Detection in Online Social Media , 2019, COMPLEX NETWORKS.

[74]  David Jurgens,et al.  A Just and Comprehensive Strategy for Using NLP to Address Online Abuse , 2019, ACL.

[75]  Björn Gambäck,et al.  Studying Generalisability across Abusive Language Detection Datasets , 2019, CoNLL.

[76]  Prasenjit Majumder,et al.  Overview of the HASOC track at FIRE 2019: Hate Speech and Offensive Content Identification in Indo-European Languages , 2019, FIRE.

[77]  Krishnaprasad Thirunarayan,et al.  Knowledge-aware Assessment of Severity of Suicide Risk for Early Intervention , 2019, WWW.

[78]  Erik Cambria,et al.  Tweeting in Support of LGBT?: A Deep Learning Approach , 2019, COMAD/CODS.

[79]  Animesh Mukherjee,et al.  HateMonitors: Language Agnostic Abuse Detection in Social Media , 2019, FIRE.

[80]  Preslav Nakov,et al.  SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval) , 2019, *SEMEVAL.

[81]  Ming-Wei Chang,et al.  BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.

[82]  Serena Villata,et al.  A System to Monitor Cyberbullying based on Message Classification and Social Network Analysis , 2019, Proceedings of the Third Workshop on Abusive Language Online.

[83]  Mona Simion,et al.  Down Girl: The Logic of Misogyny , 2020, The Philosophical Quarterly.