Resources and benchmark corpora for hate speech detection: a systematic review

Hate Speech in social media is a complex phenomenon, whose detection has recently gained significant traction in the Natural Language Processing community, as attested by several recent review works. Annotated corpora and benchmarks are key resources, considering the vast number of supervised approaches that have been proposed. Lexica play an important role as well for the development of hate speech detection systems. In this review, we systematically analyze the resources made available by the community at large, including their development methodology, topical focus, language coverage, and other factors. The results of our analysis highlight a heterogeneous, growing landscape, marked by several issues and venues for improvement.

[1]  Thomas Eckart,et al.  Building Large Monolingual Dictionaries at the Leipzig Corpora Collection: From 100 to 200 Languages , 2012, LREC.

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

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

[4]  Jing Qian,et al.  A Benchmark Dataset for Learning to Intervene in Online Hate Speech , 2019, EMNLP.

[5]  B. Lucas.  Methods for monitoring and mapping online hate speech (GSDRC Helpdesk Research Report 1121) , 2014 .

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

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

[8]  Ritesh Kumar,et al.  Benchmarking Aggression Identification in Social Media , 2018, TRAC@COLING 2018.

[9]  Lei Gao,et al.  Detecting Online Hate Speech Using Context Aware Models , 2017, RANLP.

[10]  Rogers Prates de Pelle,et al.  Offensive Comments in the Brazilian Web: a dataset and baseline results , 2017 .

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

[12]  Kush R. Varshney,et al.  The Effect of Extremist Violence on Hateful Speech Online , 2018, ICWSM.

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

[14]  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.

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

[16]  Ramit Sawhney,et al.  Detecting Offensive Tweets in Hindi-English Code-Switched Language , 2018, SocialNLP@ACL.

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

[18]  R. Plutchik.  Emotion, a psychoevolutionary synthesis , 1980 .

[19]  John Pavlopoulos,et al.  Improved Abusive Comment Moderation with User Embeddings , 2017, NLPmJ@EMNLP.

[20]  Lisa Kaati,et al.  A Study on the Feasibility to Detect Hate Speech in Swedish , 2019, 2019 IEEE International Conference on Big Data (Big Data).

[21]  Hitesh Kumar Sharma,et al.  NLP and Machine Learning Techniques for Detecting Insulting Comments on Social Networking Platforms , 2018, 2018 International Conference on Advances in Computing and Communication Engineering (ICACCE).

[22]  Tomaz Erjavec,et al.  Legal Framework, Dataset and Annotation Schema for Socially Unacceptable Online Discourse Practices in Slovene , 2017, ALW@ACL.

[23]  Alvi Md Ishmam,et al.  Hateful Speech Detection in Public Facebook Pages for the Bengali Language , 2019, 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA).

[24]  Yejin Choi,et al.  The Risk of Racial Bias in Hate Speech Detection , 2019, ACL.

[25]  Jenq-Haur Wang,et al.  Vulnerable community identification using hate speech detection on social media , 2020, Inf. Process. Manag..

[26]  Manuela Sanguinetti,et al.  Error Analysis in a Hate Speech Detection Task: The Case of HaSpeeDe-TW at EVALITA 2018 , 2019, CLiC-it.

[27]  Sérgio Nunes,et al.  A Survey on Automatic Detection of Hate Speech in Text , 2018, ACM Comput. Surv..

[28]  Hugo Lewi Hammer,et al.  Automatic Detection of Hateful Comments in Online Discussion , 2016, INISCOM.

[29]  Giovanni Vigna,et al.  Peer to Peer Hate: Hate Speech Instigators and Their Targets , 2018, ICWSM.

[30]  Viviana Patti,et al.  Time of Your Hate: The Challenge of Time in Hate Speech Detection on Social Media , 2020, Applied Sciences.

[31]  “Contro L’Odio”: A Platform for Detecting, Monitoring and Visualizing Hate Speech against Immigrants in Italian Social Media , 2020, Italian Journal of Computational Linguistics.

[32]  Rishab Nithyanand,et al.  Measuring Offensive Speech in Online Political Discourse , 2017, FOCI @ USENIX Security Symposium.

[33]  Cody Buntain,et al.  A Large Labeled Corpus for Online Harassment Research , 2017, WebSci.

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

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

[36]  Mai ElSherief,et al.  Hierarchical CVAE for Fine-Grained Hate Speech Classification , 2018, EMNLP.

[37]  Preslav Nakov,et al.  SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020) , 2020, SEMEVAL.

[38]  Michael Wiegand,et al.  A Survey on Hate Speech Detection using Natural Language Processing , 2017, SocialNLP@EACL.

[39]  Ingmar Weber,et al.  Automated Hate Speech Detection and the Problem of Offensive Language , 2017, ICWSM.

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

[41]  Felice Dell'Orletta,et al.  Hate Me, Hate Me Not: Hate Speech Detection on Facebook , 2017, ITASEC.

[42]  Barbara Kitchenham,et al.  Procedures for Performing Systematic Reviews , 2004 .

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

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

[45]  Walid Magdy,et al.  Abusive Language Detection on Arabic Social Media , 2017, ALW@ACL.

[46]  Björn Ross,et al.  Measuring the Reliability of Hate Speech Annotations: The Case of the European Refugee Crisis , 2016, ArXiv.

[47]  Ona de Gibert,et al.  Hate Speech Dataset from a White Supremacy Forum , 2018, ALW.

[48]  Ika Alfina,et al.  Hate speech detection in the Indonesian language: A dataset and preliminary study , 2017, 2017 International Conference on Advanced Computer Science and Information Systems (ICACSIS).

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

[50]  Ingmar Weber,et al.  Understanding Abuse: A Typology of Abusive Language Detection Subtasks , 2017, ALW@ACL.

[51]  Gianluca Stringhini,et al.  Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior , 2018, ICWSM.

[52]  Ben Burtenshaw,et al.  Offence in Dialogues: A Corpus-Based Study , 2019, RANLP.

[53]  Indra Budi,et al.  A Dataset and Preliminaries Study for Abusive Language Detection in Indonesian Social Media , 2018 .

[54]  Christian Kay,et al.  The Oxford English Dictionary Online , 2004, Lit. Linguistic Comput..

[55]  Taha Yasseri,et al.  Detecting weak and strong Islamophobic hate speech on social media , 2018, Journal of Information Technology & Politics.

[56]  Viviana Patti,et al.  Do You Really Want to Hurt Me? Predicting Abusive Swearing in Social Media , 2020, LREC.

[57]  Elisabetta Fersini,et al.  Unintended Bias in Misogyny Detection , 2019, 2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI).

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

[59]  Hugo Jair Escalante,et al.  Overview of MEX-A3T at IberLEF 2019: Authorship and Aggressiveness Analysis in Mexican Spanish Tweets , 2018, IberLEF@SEPLN.

[60]  Vinay Singh,et al.  A Dataset of Hindi-English Code-Mixed Social Media Text for Hate Speech Detection , 2018, PEOPLES@NAACL-HTL.

[61]  Pedro Rangel Henriques,et al.  Hate Speech Classification in Social Media Using Emotional Analysis , 2018, 2018 7th Brazilian Conference on Intelligent Systems (BRACIS).

[62]  Katharine Gelber,et al.  Evidencing the harms of hate speech , 2016 .

[63]  Viviana Patti,et al.  A New Measure of Polarization in the Annotation of Hate Speech , 2019, AI*IA.

[64]  Hatem Haddad,et al.  T-HSAB: A Tunisian Hate Speech and Abusive Dataset , 2019, ICALP.

[65]  Sérgio Nunes,et al.  A Hierarchically-Labeled Portuguese Hate Speech Dataset , 2019, Proceedings of the Third Workshop on Abusive Language Online.

[66]  Serena Villata,et al.  Cross-Platform Evaluation for Italian Hate Speech Detection , 2019, CLiC-it.

[67]  Ritesh Kumar,et al.  Aggression-annotated Corpus of Hindi-English Code-mixed Data , 2018, LREC.

[68]  Hatem Haddad,et al.  L-HSAB: A Levantine Twitter Dataset for Hate Speech and Abusive Language , 2019, Proceedings of the Third Workshop on Abusive Language Online.

[69]  Virgílio A. F. Almeida,et al.  Characterizing and Detecting Hateful Users on Twitter , 2018, ICWSM.

[70]  Zeerak Waseem,et al.  Are You a Racist or Am I Seeing Things? Annotator Influence on Hate Speech Detection on Twitter , 2016, NLP+CSS@EMNLP.

[71]  Mai ElSherief,et al.  Learning to Decipher Hate Symbols , 2019, NAACL.

[72]  Michael Wiegand,et al.  Overview of GermEval Task 2, 2019 Shared Task on the Identification of Offensive Language , 2019, KONVENS.

[73]  Silvia Bernardini,et al.  The WaCky wide web: a collection of very large linguistically processed web-crawled corpora , 2009, Lang. Resour. Evaluation.

[74]  Michael Wiegand,et al.  Inducing a Lexicon of Abusive Words – a Feature-Based Approach , 2018, NAACL.

[75]  Lei Gao,et al.  Recognizing Explicit and Implicit Hate Speech Using a Weakly Supervised Two-path Bootstrapping Approach , 2017, IJCNLP.

[76]  Xavier Giró-i-Nieto,et al.  Hate Speech in Pixels: Detection of Offensive Memes towards Automatic Moderation , 2019, ArXiv.

[77]  Thanh Vu,et al.  HSD Shared Task in VLSP Campaign 2019: Hate Speech Detection for Social Good , 2020, ArXiv.

[78]  Junyi Jessy Li,et al.  Why Swear? Analyzing and Inferring the Intentions of Vulgar Expressions , 2018, EMNLP.

[79]  Shervin Malmasi,et al.  Evaluating Aggression Identification in Social Media , 2020, TRAC.

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

[81]  Malvina Nissim,et al.  Sentiment Polarity Classification at EVALITA: Lessons Learned and Open Challenges , 2018, IEEE Transactions on Affective Computing.

[82]  Atul Kr. Ojha,et al.  Developing a Multilingual Annotated Corpus of Misogyny and Aggression , 2020, TRAC.

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

[84]  Julia Hirschberg,et al.  Detecting Hate Speech on the World Wide Web , 2012 .

[85]  Jeremy H. Clear,et al.  The British national corpus , 1993 .

[86]  Viviana Patti,et al.  Annotating Hate Speech: Three Schemes at Comparison , 2019, CLiC-it.

[87]  Tommaso Caselli,et al.  I Feel Offended, Don’t Be Abusive! Implicit/Explicit Messages in Offensive and Abusive Language , 2020, LREC.

[88]  Lee Gillam,et al.  University of Surrey Participation in TREC8: Weirdness Indexing for Logical Document Extrapolation and Retrieval (WILDER) , 1999, TREC.

[89]  Giovanni Semeraro,et al.  Computational Linguistics Against Hate: Hate Speech Detection and Visualization on Social Media in the "Contro L'Odio" Project , 2019, CLiC-it.

[90]  Maite Taboada,et al.  The SFU Opinion and Comments Corpus: A Corpus for the Analysis of Online News Comments , 2019, Corpus pragmatics : international journal of corpus linguistics and pragmatics.

[91]  Indra Budi,et al.  Multi-label Hate Speech and Abusive Language Detection in Indonesian Twitter , 2019, Proceedings of the Third Workshop on Abusive Language Online.

[92]  D. W. Sue,et al.  Racial microaggressions in everyday life: implications for clinical practice. , 2007, The American psychologist.

[93]  Felice Dell'Orletta,et al.  Overview of the EVALITA 2018 Hate Speech Detection Task , 2018, EVALITA@CLiC-it.

[94]  A Large Human-Labeled Corpus for Online Harassment Research , 2017 .

[95]  Shivakant Mishra,et al.  International Conference on Advances in Social Networks Analysis and Mining ( ASONAM ) Are They Our Brothers ? Analysis and Detection of Religious Hate Speech in the Arabic Twittersphere , 2018 .

[96]  Carlos Roberto Viana,et al.  Hate speech detection using brazilian imageboards , 2019, WebMedia.

[97]  Josef Steinberger,et al.  Cross-lingual Flames Detection in News Discussions , 2017, RANLP.

[98]  Serena Villata,et al.  A Multilingual Evaluation for Online Hate Speech Detection , 2020, ACM Trans. Internet Techn..

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