ARCHIVES

[1] N. Shawkat, J. Simpson and J. Saquer, "Evaluation of Different ML and Text Processing Techniques for Hate Speech Detection," 2022
4th International Conference on Data Intelligence and Security (ICDIS), Shenzhen, China, 2022, pp. 213-219
[2] N. S. Mullah and W. M. N. W. Zainon, "Advances in Machine Learning Algorithms for Hate Speech Detection in Social Media: A
Review," in IEEE Access, vol. 9, pp. 88364-88376, 2021
[3] B. R. Amrutha and K. R. Bindu, "Detecting Hate Speech in Tweets Using Different Deep Neural Network Architectures," 2019
International Conference on Intelligent Computing and Control Systems (ICCS), Madurai, India, 2019, pp. 923-926
[4] G. H. Panchala, V. V. S Sasank, D. R. HarshithaAdidela, P. Yellamma, K. Ashesh and C. Prasad, "Hate Speech & Offensive Language
Detection Using ML &NLP," 2022 4th International Conference on Smart Systems and Inventive Technology (ICSSIT), Tirunelveli,
India, 2022, pp. 1262-1268,
[5] P. K. Roy, A. K. Tripathy, T. K. Das and X. -Z. Gao, "A Framework for Hate Speech Detection Using Deep Convolutional Neural
Network," in IEEE Access, vol. 8, pp. 204951-204962, 2020
[6] Rahul, V. Gupta, V. Sehra and Y. R. Vardhan, "Ensemble Based Hinglish Hate Speech Detection," 2021 5th International Conference
on Intelligent Computing and Control Systems (ICICCS), Madurai, India, 2021, pp. 1800-1806
[7] M. U. S. Khan, A. Abbas, A. Rehman and R. Nawaz, "HateClassify: A Service Framework for Hate Speech Identification on Social
Media," in IEEE Internet Computing, vol. 25, no. 1, pp. 40-49, 1 Jan.-Feb. 2021
[8] Rahul, V. Gupta, V. Sehra and Y. R. Vardhan, "Hindi-English Code Mixed Hate Speech Detection using Character Level
Embeddings," 2021 5th International Conference on Computing Methodologies and Communication (ICCMC), Erode, India, 2021,
pp. 1112-1118
[9] U. A. N. Rohmawati, S. W. Sihwi and D. E. Cahyani, "SEMAR: An Interface for Indonesian Hate Speech Detection Using Machine
Learning," 2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), Yogyakarta, Indonesia, 2018, pp. 646-651
[10] O. Oriola and E. Kotzé, "Evaluating Machine Learning Techniques for Detecting Offensive and Hate Speech in South African
Tweets," in IEEE Access, vol. 8, pp. 21496-21509, 2020
[11] S. A. Kokatnoor and B. Krishnan, "Twitter Hate Speech Detection using Stacked Weighted Ensemble (SWE) Model," 2020 Fifth
International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN), Bangalore, India,
2020, pp. 87-92
[12] H. Rathpisey and T. B. Adji, "Handling Imbalance Issue in Hate Speech Classification using Sampling-based Methods," 2019 5th
International Conference on Science in Information Technology (ICSITech), Yogyakarta, Indonesia, 2019, pp. 193-198
[13] K. Mnassri, P. Rajapaksha, R. Farahbakhsh and N. Crespi, "BERT-based Ensemble Approaches for Hate Speech Detection,"
GLOBECOM 2022 - 2022 IEEE Global Communications Conference, Rio de Janeiro, Brazil, 2022, pp. 4649-4654
[14] H. S. Alatawi, A. M. Alhothali and K. M. Moria, "Detecting White Supremacist Hate Speech Using Domain Specific Word Embedding
With Deep Learning and BERT," in IEEE Access, vol. 9, pp. 106363-106374, 2021
[15] A. Rodriguez, Y. -L. Chen and C. Argueta, "FADOHS: Framework for Detection and Integration of Unstructured Data of Hate
Speech on Facebook Using Sentiment and Emotion Analysis," in IEEE Access, vol. 10, pp. 22400-22419, 2022
[16] M. Bilal, A. Khan, S. Jan and S. Musa, "Context-Aware Deep Learning Model for Detection of Roman Urdu Hate Speech on Social
Media Platform," in IEEE Access, vol. 10, pp. 121133-121151, 2022
[17] B. Pariyani, K. Shah, M. Shah, T. Vyas and S. Degadwala, "Hate Speech Detection in Twitter using Natural Language Processing,"
2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV), Tirunelveli,
India, 2021, pp. 1146-1152
[18] H. Sohn and H. Lee, "MC-BERT4HATE: Hate Speech Detection using Multi-channel BERT for Different Languages and
Translations," 2019 International Conference on Data Mining Workshops (ICDMW), Beijing, China, 2019, pp. 551-559
[19] S. W. A. M. D. Samarasinghe, R. G. N. Meegama and M. Punchimudiyanse, "Machine Learning Approach for the Detection of Hate
Speech in Sinhala Unicode Text," 2020 20th International Conference on Advances in ICT for Emerging Regions (ICTer), Colombo,
Sri Lanka, 2020, pp. 65-70
[20] C. Baydogan and B. Alatas, "Metaheuristic Ant Lion and Moth Flame Optimization-Based Novel Approach for Automatic Detection
of Hate Speech in Online Social Networks," in IEEE Access, vol. 9, pp. 110047-110062, 2021
[21] S. Khan, M. Fazil and A. R. Baig, “BiCHAT: BiLSTM with deep CNN and hierarchical attention for hate speech detection”, Journal
of King Saud University - Computer and Information Sciences, vol. 34, no. 7, pp. 4335-4344, 21 May 2022
[22] N. Badri, F. Kboubi and A. H. Chaibi, “Combining FastText and Glove Word Embedding for Offensive and Hate speech Text
Detection”, Procedia Computer Science, vol. 207, no. 12, pp. 769-778, 19 October 2022
[23] P. Sharmila, K. S. M. Anbananthen, D. Chelliah, S. Parthasarathy and S. Kannan, "PDHS: Pattern-Based Deep Hate Speech
Detection With Improved Tweet Representation," in IEEE Access, vol. 10, pp. 105366-105376, 2022