Hate Lingo: A Target-Based Linguistic Analysis of Hate Speech in Social Media

The Berkeley FrameNet Project

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Automated Hate Speech Detection and the Problem of Offensive Language

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Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter

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A Survey on Hate Speech Detection using Natural Language Processing

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Abusive Language Detection in Online User Content

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Named Entity Recognition in Tweets: An Experimental Study

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FrameNet II: Extended theory and practice

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Is the Sample Good Enough? Comparing Data from Twitter's Streaming API with Twitter's Firehose

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Big questions for social media big data: Representativeness, validity and other methodological pitfalls

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Hate Speech Detection with Comment Embeddings

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Social Media, Echo Chambers, and Political Polarization

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Developing an online hate classifier for multiple social media platforms

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Misinformation, Disinformation, and Online Propaganda

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Vulnerable community identification using hate speech detection on social media

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A Benchmark Dataset for Learning to Intervene in Online Hate Speech

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SoK: Hate, Harassment, and the Changing Landscape of Online Abuse

Thomas, K., Akhawe, D., Bailey, M., Boneh, D., Bursztein, E., Consolvo, S., Dell, N. L., Durumeric, Z., Kelley, P. G., Kumar, D., et al. (2021) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp40001.2021.00028 · Cited by 159

A Literature Review of Textual Hate Speech Detection Methods and Datasets

Alkomah, F., & Ma, X. (2022) · Information · doi:10.3390/info13060273 · Cited by 167

‘Welcome to #GabFam’: Far-right virtual community on Gab

Jasser, G., McSwiney, J., Pertwee, E., & Zannettou, S. (2021) · New Media & Society · doi:10.1177/14614448211024546 · Cited by 158

A Framework for the Computational Linguistic Analysis of Dehumanization

Mendelsohn, J., Tsvetkov, Y., & Jurafsky, D. (2020) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2020.00055 · Cited by 148

Facts and Where to Find Them: Empirical Research on Internet Platforms and Content Moderation

Keller, D., & Leerssen, P. (2020) · Data Archiving and Networked Services (DANS) · doi:10.1017/9781108890960

Online Hate Speech

Siegel, A. A. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.005 · Cited by 123

DeepHateExplainer: Explainable Hate Speech Detection in Under-resourced Bengali Language

Karim, M. R., Dey, S. K., Islam, T., Sarker, S., Menon, M. H., Hossain, K., Hossain, M. A., & Decker, S. (2021) · IEEE International Conference on Data Science and Advanced Analytics (DSAA) · doi:10.1109/dsaa53316.2021.9564230 · Cited by 121

Automatic Classification of Sexism in Social Networks: An Empirical Study on Twitter Data

Rodríguez-Sanchez, F. J., Carrillo‐de‐Albornoz, J., & Plaza, L. (2020) · IEEE Access · doi:10.1109/access.2020.3042604 · Cited by 121

A Quantitative Approach to Understanding Online Antisemitism

Zannettou, S., Finkelstein, J., Bradlyn, B., & Blackburn, J. (2020) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v14i1.7343 · Cited by 104

Assessing the Extent and Types of Hate Speech in Fringe Communities: A Case Study of Alt-Right Communities on 8chan, 4chan, and Reddit

Rieger, D., Kümpel, A. S., Wich, M., Kiening, T., & Groh, G. (2021) · Social Media + Society · doi:10.1177/20563051211052906 · Cited by 102

Classification Benchmarks for Under-resourced Bengali Language based on Multichannel Convolutional-LSTM Network

Karim, M. R., Chakravarthi, B. R., McCrae, J. P., & Cochez, M. (2020) · IEEE International Conference on Data Science and Advanced Analytics (DSAA) · doi:10.1109/dsaa49011.2020.00053 · Cited by 108

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

Pamungkas, E. W., & Patti, V. (2019) · Annual Meeting of the Association for Computational Linguistics: Student Research Workshop (ACL SRW) · doi:10.18653/v1/p19-2051 · Cited by 98

Bots and online hate during the COVID-19 pandemic: case studies in the United States and the Philippines

Uyheng, J., & Carley, K. M. (2020) · Journal of Computational Social Science · doi:10.1007/s42001-020-00087-4 · Cited by 105

"You Know What to Do"

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“Thought I’d Share First” and Other Conspiracy Theory Tweets from the COVID-19 Infodemic: Exploratory Study

Gerts, D., Shelley, C. D., Parikh, N., Pitts, T., Ross, C. W., Fairchild, G. C., Chavez, N. Y. V., & Daughton, A. R. (2021) · JMIR Public Health and Surveillance · doi:10.2196/26527 · Cited by 84

FERMI at SemEval-2019 Task 5: Using Sentence embeddings to Identify Hate Speech Against Immigrants and Women in Twitter

Indurthi, V., Syed, B., Shrivastava, M., Chakravartula, N., Gupta, M., & Varma, V. (2019) · International Workshop on Semantic Evaluation (SemEval) · doi:10.18653/v1/s19-2009 · Cited by 83

Racism is a Virus: Anti-Asian Hate and Counterhate in Social Media during the COVID-19 CrisisPreprint

Ziems, C., He, B., Soni, S., & Kumar, S. (2020) · arXiv (Cornell University) · Cited by 81

Systematic review of determinants and consequences of bystander interventions in online hate and cyberbullying among adults

Rudnicki, K., Vandebosch, H., Voué, P., & Poels, K. (2022) · Behaviour and Information Technology · doi:10.1080/0144929x.2022.2027013 · Cited by 80

Twitter Hate Speech Detection: A Systematic Review of Methods, Taxonomy Analysis, Challenges, and Opportunities

Mansur, Z., Omar, N., & Tiun, S. B. (2023) · IEEE Access · doi:10.1109/access.2023.3239375 · Cited by 77

Hate speech detection in social media: Techniques, recent trends, and future challenges

Rawat, A., Kumar, S., & Samant, S. S. (2024) · Wiley Interdisciplinary Reviews Computational Statistics · doi:10.1002/wics.1648 · Cited by 70

Toxic language in online incel communities

Pelzer, B., Kaati, L., Cohen, K., & Fernquist, J. (2021) · SN Social Sciences · doi:10.1007/s43545-021-00220-8 · Cited by 89

Democratic Transparency in the Platform Society

Gorwa, R., & Ash, T. G. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.013 · Cited by 71

Nikolov-Radivchev at SemEval-2019 Task 6: Offensive Tweet Classification with BERT and Ensembles

Nikolov, A., & Radivchev, V. (2019) · International Workshop on Semantic Evaluation (SemEval) · doi:10.18653/v1/s19-2123 · Cited by 72

Misinformation and Its Correction

Wittenberg, C., & Berinsky, A. J. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.009 · Cited by 64

Multimodal Hate Speech Detection from Bengali Memes and Texts

Karim, M. R., Dey, S. K., Islam, T., Shajalal, M., & Chakravarthi, B. R. (2023) · Communications in computer and information science · doi:10.1007/978-3-031-33231-9_21 · Cited by 65

Analyzing the hate and counter speech accounts on TwitterPreprint

Mathew, B., Kumar, N. R., Ravina, R., Goyal, P., & Mukherjee, A. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1812.02712 · Cited by 58

SoK: Content Moderation in Social Media, from Guidelines to Enforcement, and Research to Practice

Singhal, M., Ling, C., Paudel, P., Thota, P., Kumarswamy, N., Stringhini, G., & Nilizadeh, S. (2023) · 2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P) · doi:10.1109/eurosp57164.2023.00056 · Cited by 57

AngryBERT: Joint Learning Target and Emotion for Hate Speech Detection

Awal, R., Cao, R., Lee, R. K.-W., & Mitrović, S. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-75762-5_55 · Cited by 60

Characterizing network dynamics of online hate communities around the COVID-19 pandemic

Uyheng, J., & Carley, K. M. (2021) · Applied Network Science · doi:10.1007/s41109-021-00362-x · Cited by 65

SocialHaterBERT: A dichotomous approach for automatically detecting hate speech on Twitter through textual analysis and user profiles

del Valle-Cano, G., Quijano-Sánchez, L., Liberatore, F., & Gómez, J. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.119446 · Cited by 63

HateGAN: Adversarial Generative-Based Data Augmentation for Hate Speech Detection

Cao, R., & Lee, R. K.-W. (2020) · International Conference on Computational Linguistics · doi:10.18653/v1/2020.coling-main.557 · Cited by 53

ConvAI at SemEval-2019 Task 6: Offensive Language Identification and Categorization with Perspective and BERT

Pavlopoulos, J., Thain, N., Dixon, L., & Androutsopoulos, I. (2019) · International Workshop on Semantic Evaluation (SemEval) · doi:10.18653/v1/s19-2102 · Cited by 52

Detectando el odio ideológico en Twitter. Desarrollo y evaluación de un detector de discurso de odio por ideología política en tuits en español

Amores, J. J., Blanco‐Herrero, D., Holgado, P. S., & Frías-Vázquez, M. (2021) · Cuadernos info · doi:10.7764/cdi.49.27817 · Cited by 48

How epidemic psychology works on Twitter: evolution of responses to the COVID-19 pandemic in the U.S.

Aiello, L. M., Quercia, D., Zhou, K., Constantinides, M., Šćepanović, S., & Joglekar, S. P. (2021) · Humanities and Social Sciences Communications · doi:10.1057/s41599-021-00861-3 · Cited by 52

"A Virus Has No Religion": Analyzing Islamophobia on Twitter During the COVID-19 Outbreak

Chandra, M., Reddy, M., Sehgal, S., Gupta, S., Buduru, A. B., & Kumaraguru, P. (2021) · ACM Conference on Hypertext and Social Media (HT) · doi:10.1145/3465336.3475111 · Cited by 46

Challenges of Moderating Social Virtual Reality

Sabri, N., Chen, B., Teoh, A., Dow, S. P., Vaccaro, K., & ElSherief, M. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581329 · Cited by 45

ChamberBreaker: Mitigating the Echo Chamber Effect and Supporting Information Hygiene through a Gamified Inoculation System

Jeon, Y., Kim, B., Xiong, A., Lee, D., & Han, K. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3479859 · Cited by 45

Understanding Visual Memes: An Empirical Analysis of Text Superimposed on Memes Shared on Twitter

Du, Y., Masood, M. A., & Joseph, K. (2020) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v14i1.7287 · Cited by 42

A Deep Learning Framework for the Detection of Malay Hate Speech

Maity, K., Bhattacharya, S., Saha, S., & Seera, M. (2023) · IEEE Access · doi:10.1109/access.2023.3298808 · Cited by 44

Bots and Computational Propaganda: Automation for Communication and Control

Woolley, S. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.006 · Cited by 41

Towards a Comprehensive Taxonomy and Large-Scale Annotated Corpus for Online Slur Usage

Kurrek, J., Saleem, H. M., & Ruths, D. A. (2020) · Workshop on Online Abuse and Harms (WOAH) · doi:10.18653/v1/2020.alw-1.17 · Cited by 38

Facts and Where to Find Them: Empirical Research on Internet Platforms and Content Moderation

Keller, D., & Leerssen, P. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.011 · Cited by 39

Sequential targeting: A continual learning approach for data imbalance in text classification

Jang, J., Kim, Y., Choi, K.-H., & Suh, S. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2021.115067 · Cited by 44

A Deep Dive into Multilingual Hate Speech Classification

Aluru, S. S., Mathew, B., Saha, P., & Mukherjee, A. (2021) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-67670-4_26 · Cited by 37

Automatic Identification of Harmful, Aggressive, Abusive, and Offensive Language on the Web: A Survey of Technical Biases Informed by Psychology Literature

Balayn, A., Yang, J., Szlávik, Z., & Bozzon, A. (2021) · ACM Transactions on Social Computing · doi:10.1145/3479158 · Cited by 38

Hate Speech and Counter Speech Detection: Conversational Context Does Matter

Yu, X., Blanco, E., & Hong, L. (2022) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2022.naacl-main.433 · Cited by 34

An Investigation of Large Language Models for Real-World Hate Speech Detection

Guo, K., Hu, A., Mu, J., Shi, Z., Zhao, Z., Vishwamitra, N., & Hu, H. (2023) · International Conference on Machine Learning and Applications · doi:10.1109/icmla58977.2023.00237 · Cited by 68

Democratic Creative Destruction? The Effect of a Changing Media Landscape on Democracy

Nielsen, R. K., & Fletcher, R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.008 · Cited by 35

Comparing the Language of QAnon-Related Content on Parler, Gab, and Twitter

Sipka, A., Hannák, A., & Urman, A. (2021) · Web Science Conference · doi:10.1145/3501247.3531550 · Cited by 36

Towards offensive language detection and reduction in four Software Engineering communities

Cheriyan, J., Savarimuthu, B. T. R., & Cranefield, S. (2021) · International Conference on Evaluation and Assessment in Software Engineering (EASE) · doi:10.1145/3463274.3463805 · Cited by 37

Hate Speech in the Political Discourse on Social Media: Disparities Across Parties, Gender, and Ethnicity

Solovev, K., & Pröllochs, N. (2022) · International World Wide Web Conference (WWW) · doi:10.1145/3485447.3512261 · Cited by 31

Political Hate Speech Detection and Lexicon Building: A Study in Taiwan

Wang, C., Day, M.-Y., & Wu, C.-L. (2022) · IEEE Access · doi:10.1109/access.2022.3160712 · Cited by 33

Misogynoir: challenges in detecting intersectional hate

Kwarteng, J., Perfumi, S. C., Farrell, T., Third, A., & Fernandez, M. (2022) · Social Network Analysis and Mining · doi:10.1007/s13278-022-00993-7 · Cited by 30

THAR- Targeted Hate Speech Against Religion: A high-quality Hindi-English code-mixed Dataset with the Application of Deep Learning Models for Automatic Detection

Sharma, D., Singh, A., & Singh, V. K. (2024) · ACM Transactions on Asian and Low-Resource Language Information Processing · doi:10.1145/3653017 · Cited by 34

Exploring hate speech dynamics: The emotional, linguistic, and thematic impact on social media users

Ghenai, A., Noorian, Z., Moradisani, H., Abadeh, P., Erentzen, C. A., & Zarrinkalam, F. (2025) · Information Processing & Management · doi:10.1016/j.ipm.2025.104079 · Cited by 38

Towards Measuring Adversarial Twitter Interactions against Candidates in the US Midterm Elections

Hua, Y., Ristenpart, T., & Naaman, M. (2020) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v14i1.7298 · Cited by 29

Hate begets Hate: A Temporal Study of Hate SpeechPreprint

Mathew, B., Illendula, A., Saha, P., Sarkar, S., Goyal, P., & Mukherjee, A. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1909.10966 · Cited by 29

A Method to Analyze Multiple Social Identities in Twitter Bios

Pathak, A., Madani, N., & Joseph, K. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3479502 · Cited by 32

The Economics of Content Moderation: Theory and Experimental Evidence from Hate Speech on TwitterPreprint

Jiménez-Durán, R. (2022) · Social Science Research Network · doi:10.2139/ssrn.4044098 · Cited by 35

Comparative Media Regulation in the United States and Europe

Fukuyama, F., & Grotto, A. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.010 · Cited by 28

How to Detect Online Hate towards Migrants and Refugees? Developing and Evaluating a Classifier of Racist and Xenophobic Hate Speech Using Shallow and Deep Learning

Calderón, C. A., Amores, J. J., Holgado, P. S., Vrysis, L., Vryzas, N., & Alonso, M. O. (2022) · Sustainability · doi:10.3390/su142013094 · Cited by 26

Comparative Evaluation of Label-Agnostic Selection Bias in Multilingual Hate Speech Datasets

Ousidhoum, N. D., Song, Y., & Yeung, D. (2020) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.199 · Cited by 26

Online Political Advertising in the United States

Fowler, E. F., Franz, M. M., & Ridout, T. N. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.007 · Cited by 26

Interpretable Multi-Modal Hate Speech DetectionPreprint

Vijayaraghavan, P., Larochelle, H., & Roy, D. K. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.01616 · Cited by 25

Towards Automatic Detection and Explanation of Hate Speech and Offensive Language

Dorris, W., Hu, R., Vishwamitra, N., Luo, F., & Costello, M. (2020) · doi:10.1145/3375708.3380312 · Cited by 24

He said “who’s gonna take care of your children when you are at ACL?”: Reported Sexist Acts are Not Sexist

Chiril, P., Moriceau, V., Benamara, F., Mari, A., Origgi, G., & Coulomb‐Gully, M. (2020) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2020.acl-main.373 · Cited by 26

Hate Speech as an Indicator for the State of the Society

Schäfer, S., Sülflow, M., & Reiners, L. (2021) · Journal of Media Psychology Theories Methods and Applications · doi:10.1027/1864-1105/a000294 · Cited by 28

Opinion Conflicts

Maity, S., Chakraborty, A., Goyal, P., & Mukherjee, A. (2018) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3274386 · Cited by 43

A New Hate Speech Detection System based on Textual and Psychological Features

Alkomah, F., Salati, S., & Ma, X. (2022) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2022.01308100 · Cited by 23

Online offensive behaviour in socialmedia: Detection approaches, comprehensive review and future directions

Chinivar, S., Roopa, M. S., Arunalatha, J. S., & Venugopal, K. R. (2022) · Entertainment Computing · doi:10.1016/j.entcom.2022.100544 · Cited by 25

Fully Connected Neural Network with Advance Preprocessor to Identify Aggression over Facebook and Twitter

Raiyani, K., Gonçalves, T., Quaresma, P., & Nogueira, V. (2018) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · Cited by 23

Conclusion: The Challenges and Opportunities for Social Media Research

Persily, N., & Tucker, J. A. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.014 · Cited by 24

Us vs. Them: A Dataset of Populist Attitudes, News Bias and Emotions

Cabot, ‪.-L. H., Abadi, D., Fischer, A. H., & Shutova, E. (2021) · Conference of the European Chapter of the Association for Computational Linguistics · doi:10.18653/v1/2021.eacl-main.165 · Cited by 27

Indonesian Tweets Hate Speech Target Classification using Machine Learning

Kurniawan, S. V., & Budi, I. D. (2020) · International Conference on Informatics and Computing (ICIC) · doi:10.1109/icic50835.2020.9288515 · Cited by 21

From Dogwhistles to Bullhorns: Unveiling Coded Rhetoric with Language Models

Mendelsohn, J., Bras, R. J. L., Choi, Y., & Sap, M. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-long.845 · Cited by 33

MetaHate: A Dataset for Unifying Efforts on Hate Speech Detection

Piot, P., Martín-Rodilla, P., & Parapar, J. (2024) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v18i1.31445 · Cited by 21

Proceedings of the 5th Workshop on Online Abuse and Harms (WOAH 2021)

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Platform-agnostic Model to Detect Sinophobia on Social Media

Morgan, M., & Kulkarni, A. (2023) · ACM Southeast Regional Conference (ACMSE) · doi:10.1145/3564746.3587024 · Cited by 19

jhan014 at SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media

Han, J., Wu, S., & Liu, X. (2019) · International Workshop on Semantic Evaluation (SemEval) · doi:10.18653/v1/s19-2116 · Cited by 18

Utilization of social media in Learning Islamic Religion: Its Impact on Strengthening Student Outcomes and Achievements

Minarti, M., Rahmah, M. N., Khalilurrahman, K., Samsir, S., & Mardiana, M. (2023) · Nidhomul Haq Jurnal Manajemen Pendidikan Islam · doi:10.31538/ndh.v8i2.3930 · Cited by 18

Evaluating transfer learning approach for detecting Arabic anti-refugee/migrant speech on social media

Mohdeb, D., Laifa, M., Zerargui, F., & Benzaoui, O. (2022) · Aslib Journal of Information Management · doi:10.1108/ajim-10-2021-0293 · Cited by 20

The Economics of Content Moderation: Theory and Experimental Evidence from Hate Speech on TwitterPreprint

Jiménez-Durán, R. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4590147 · Cited by 18

KnowMeme: A Knowledge-enriched Graph Neural Network Solution to Offensive Meme Detection

Shang, L., Youn, C., Zha, Y., Zhang, Y., & Wang, D. (2021) · IEEE International Conference on eScience · doi:10.1109/escience51609.2021.00029 · Cited by 18

A review on abusive content automatic detection: approaches, challenges and opportunities

Alrashidi, B., Jamal, A. T., Khan, I., & Alkhathlan, A. (2022) · PeerJ Computer Science · doi:10.7717/peerj-cs.1142 · Cited by 20

Using Deep Learning to Detect Islamophobia on Reddit

Aldreabi, E., Lee, J. M., & Blackburn, J. (2023) · Proceedings of the ... International Florida Artificial Intelligence Research Society Conference · doi:10.32473/flairs.36.133324 · Cited by 16

How Hate Speech Varies by Target Identity: A Computational Analysis

Yoder, M. M., Ng, L. H. X., Brown, D. W., & Carley, K. M. (2022) · Conference on Computational Natural Language Learning · doi:10.18653/v1/2022.conll-1.3 · Cited by 20

Detecting Online Hate Speech: Approaches Using Weak Supervision and Network Embedding Models

Ridenhour, M., Bagavathi, A., Raisi, E., & Krishnan, S. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-61255-9_20 · Cited by 15

Levels of hate in online environments

Berglind, T., Pelzer, B., & Kaati, L. (2019) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1145/3341161.3343521 · Cited by 17

Opinion Conflicts: An Effective Route to Detect Incivility in TwitterPreprint

Maity, S. K., Chakraborty, A., Goyal, P., & Mukherjee, A. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1809.00289 · Cited by 15

The Effects of Social Approval Signals on the Production of Online Hate: A Theoretical Explication

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