Automatic Hate Speech Detection: A Literature Review

  • Mohiyaddeen Student, Department of Computer Science, Integral University, INDIA
  • Dr. Sifatullah Siddiqi Professor, Department of Computer Science, Integral University, INDIA
Keywords: Classification Algorithm, Machine Learning, Hate Speech, Deep Learning, Supervised Learning


Hate speech has been an ongoing problem on the Internet for many years. Besides, social media, especially Facebook, and Twitter have given it a global stage where those hate speeches can spread far more rapidly. Every social media platform needs to implement an effective hate speech detection system to remove offensive content in real-time. There are various approaches to identify hate speech, such as Rule-Based, Machine Learning based, deep learning based and Hybrid approach. Since this is a review paper, we explained the valuable works of various authors who have invested their valuable time in studying to identifying hate speech using various approaches.


Download data is not yet available.


E. Spertus. (1997). Smokey: automatic recognition of hostile messages. In: Innov. Appl. Artif. Intell. - Conf. Proc., pp. 1058–1065.

A. Abbasi & H. Chen. (2007). Affect intensity analysis of dark web forums. In: IEEE Intell. Secur. Informatics, pp. 282–288, 2007. DOI: 10.1109/isi.2007.379486.

H. Watanabe, M. Bouazizi, & T. Ohtsuki. (2018). Hate speech on twitter: A pragmatic approach to collect hateful and offensive expressions and perform hate speech detection. IEEE Access, 6, 13825–13835.

F. Rodriguez-Sanchez, J. Carrillo-de-Albornoz, & L. Plaza. (2020). Automatic classification of sexism in social networks: An empirical study on Twitter data. IEEE Access, 219563–219576. DOI: 10.1109/ACCESS.2020.3042604.

O. Oriola & E. Kotze. (2020). Evaluating machine learning techniques for detecting offensive and hate speech in South African tweets. IEEE Access, 8, 21496–21509. DOI: 10.1109/ACCESS.2020.2968173.

R. Cohen-Almagor. (2011). Fighting hate and bigotry on the internet. Policy & Internet, 3(3), 89–114.

N. Sambuli, F. Morara, & C. Mahihu. (2013). Umati: Monitoring online dangerous speech. Available at:

Z. Waseem & D. Hovy. (2016). Hateful symbols or hateful people? Predictive features for hate speech detection on Twitter.

A. Founta et al. (2018). Large scale crowdsourcing and characterization of twitter abusive behavior. No. Icwsm, 491–500.

M. O. Ibrohim. (2019). Multi-label Hate Speech and Abusive Language Detection in Indonesian Twitter.

Ç. Çöltekin. (2020). A corpus of Turkish offensive language on social media, pp. 6174–6184.

M. H. Ribeiro, P. H. Calais, Y. A. Santos, V. A. F. Almeida, & W. Meira. (2018). Characterizing and detecting hateful users on Twitter. arXiv, Icwsm, 676–679.

P. Liu, W. Li, & L. Zou. (2019). NULI at semeval-2019 task 6: Transfer learning for offensive language detection using bidirectional transformers. DOI: 10.18653/v1/s19-2011.

S. D. Swamy, A. Jamatia, & B. Gambäck. (2019). Studying generalisability across abusive language detection datasets. In: CoNLL 2019 - 23rd Conf. Comput. Nat. Lang. Learn. Proc. Conf., pp. 940–950. DOI: 10.18653/v1/k19-1088.

R. Kshirsagar, T. Cukuvac, K. McKeown, & S. McGregor. (2018). Predictive embeddings for hate speech detection on twitter. arXiv. DOI: 10.18653/v1/w18-5104.

P. Mishra, H. Yannakoudakis, & E. Shutova. (2018). Neural character-based composition models for abuse detection. In: arXiv.

J. Mitrović, B. Birkeneder, & M. Granitzer. (2015). nlpUP at SemEval-2019 task 6: A deep neural language model for offensive language detection, pp. 722–726. DOI: 10.18653/v1/s19-2127.

C. J. Hutto & E. Gilbert. (2014). VADER : A parsimonious rule-based model for sentiment analysis of social media text In: Proceedings of the Eighth International AAAI Conference on Weblogs and Social Media, pp. 216–225.

N. D. Gitari, Z. Zuping, H. Damien, & J. Long. (2015). A lexicon-based approach for hate speech detection. IJMUE, 10(4), 215–230.

N. R. Fatahillah, P. Suryati, & C. Haryawan. (2018). Implementation of naive bayes classifier algorithm on social media (Twitter) to the teaching of Indonesian hate speech. In: Proc. - 2017 Int. Conf. Sustain. Inf. Eng. Technol. SIET 2017, pp. 128–131. DOI: 10.1109/SIET.2017.8304122.

M. A. Fauzi & A. Yuniarti. (2018). Ensemble method for indonesian twitter hate speech detection. IJEECS, 294–299. DOI: 10.11591/ijeecs.v11.i1.pp294-299.

P. Sari & B. Ginting. (2019). Hate speech detection on twitter using multinomial logistic regression classification method, pp. 105–111.

A. Briliani, B. Irawan, & C. Setianingsih. (2019). Hate speech detection in indonesian language on instagram comment section using K-nearest neighbor classification method. In: Proc. - 2019 IEEE Int. Conf. Internet Things Intell. Syst. IoTaIS 2019, pp. 98–104. DOI: 10.1109/IoTaIS47347.2019.8980398.

R. Zhao & K. Mao. (2016). Cyberbullying detection based on semantic-enhanced marginalized denoising. DOI: 10.1109/TAFFC.2016.2531682.

A. Rodriguez, C. Argueta, & Y. L. Chen. (2019). Automatic Detection of Hate Speech on Facebook Using Sentiment and Emotion Analysis. In: 1st Int. Conf. Artif. Intell. Inf. Commun. ICAIIC 2019, pp. 169–174. DOI: 10.1109/ICAIIC.2019.8669073.

S. Jaki & T. De Smedt. (2018). Right-wing German hate speech on twitter : Analysis and automatic detection, pp. 1–31.

M. Di Capua, E. Di Nardo, & A. Petrosino. (2016). Unsupervised cyber bullying detection in social networks, pp. 432–437.

H. Rosa, D. Matos, L. Coheur, & P. Carvalho. (2018). A ‘Deeper’ look at detecting cyberbullying in social networks. In: 2018 Int. Jt. Conf. Neural Networks, pp. 1–8. DOI: 10.1109/IJCNN.2018.8489211.

T. Van Huynh, D. Nguyen, K. Van Nguyen, N. L. Nguyen, & A. G. Nguyen. (2019). Hate speech detection on vietnamese social media text using the Bi-GRU-LSTM-CNN Model.

B. Gambäck & U. K. Sikdar. (2017). Using convolutional neural networks to classify hate-speech. No. 7491, 85–90.

E. W. Pamungkas, V. Patti, & D. Informatica. (2019). Cross-domain and cross-lingual abusive language detection : A hybrid approach with deep learning and a multilingual lexicon, pp. 363–370.

S. Alsafari, S. Sadaoui, & M. Mouhoub. (2020). Hate and offensive speech detection on Arabic social media. Online Soc. Networks Media, 19, 100096, 2020. DOI: 10.1016/j.osnem.2020.100096.

How to Cite
Mohiyaddeen, & Dr. Sifatullah Siddiqi. (2021). Automatic Hate Speech Detection: A Literature Review. International Journal of Engineering and Management Research, 11(2), 116-121.