1
Computer Engineering, Sanjivani College of Engineering, Kopargoan, Savitribai Phule Pune University, India.
(rupeshchaudhari2151@gmail.com,)
2
Computer Engineering, Sanjivani College of Engineering, Kopargoan, Savitribai Phule Pune University, India.
(ritikgade22@gmail.com)
3
Computer Engineering, Sanjivani College of Engineering, Kopargoan, Savitribai Phule Pune University, India.
(pranavgawali2510@gmail.com)
4
Computer Engineering, Sanjivani College of Engineering, Kopargoan, Savitribai Phule Pune University, India.
(mangeshgite9@gmail.com)
5
Computer Engineering, Sanjivani College of Engineering, Kopargoan, Savitribai Phule Pune University, India.
(pawaranilcomp@sanjivani.org.in)
Abstract :
There is an enormous growth of social media which fully promotes freedom of expression through its
anonymity feature. Freedom of expression is a human right but hate speech towards a person or group
based on race, caste, religion, ethnic or national origin, sex, disability, gender identity, etc. is an abuse of
this sovereignty. It seriously promotes violence or hate crimes and creates an imbalance in society by
damaging peace, credibility, and human rights, etc. To overcome this problem, the hate speech detection
model is made which will classify the speech and if the speech used by user is containing hate word, it
will be detected and system will sent an alert message to user about it. In order to solve various hate
speech problems we use some of the machine learning algorithms such as logistic regression and random
forest. If user disrupts cyber guidelines, then strict action shall be taken and user’s account will be ban
forever. This help to reduce cyber crimes in effective and efficient manner.
Keywords :
Machine learning , Hate speech , Natural language processing , Data pre-processing , Random forest ,
Logistic regression , Hate word classification.
References :
[1] Schmidt, Anna Wiegand, Michael, ”A Survey on Hate Speech Detection using Natural Language Processing”, 1-
10. 10.18653/v1/W17-1101. URL : https://aclanthology.org/W17-1101 , (2017).
[2] H. Watanabe, M. Bouazizi and T. Ohtsuki, ”Hate Speech on Twitter: A Pragmatic Approach to Collect Hateful
and Offensive Expressions and Perform Hate Speech Detection,” in IEEE Access, vol. 6, pp. 13825-13835,
2018, doi: 10.1109/ACCESS.2018.2806394.
[3] Stephen Wermiel, ”The Ongoing Challenge to Define Free Speech”, 43 Human Rights 82 (2018).
[4] MacAvaney S, Yao H-R, Yang E, Russell K, Goharian N, Frieder O, ”Hate speech detection: Challenges and
solutions”, PLoS ONE 14(8): e0221152, https://doi.org/10.1371/journal.pone.0221152 , (2019).
[5] Vu, Xuan-Son Vu, Thanh Tran, Mai-Vu Le-Cong, Thanh Nguyen, Huyen, ”HSD Shared Task in VLSP
Campaign 2019:Hate Speech Detection for Social Good”,(2020).
[6] ’Twitter’ Website, 2021, The Twitter Rules, Retrieved from this site: https://support.twitter.com/articles/.
[7]’Youtube’ Website, 2021, Hate speech, Retrieved from this site :
https://support.google.com/youtube/answer/2801939?hl=en
[8] K. A. Qureshi and M. Sabih, ”Un-Compromised Credibility: Social Media Based Multi-Class Hate Speech
Classification for Text”, in IEEE Access, vol. 9, pp. 109465-109477, 2021, doi:
10.1109/ACCESS.2021.3101977.
[9] Mathew, Binny, et al. "Analyzing the hate and counter speech accounts on twitter." arXiv preprint
arXiv:1812.02712 ,url- https://doi.org/10.48550/arXiv.1812.02712 (2018).
[10] P. Kavitha , R. Subha Shini , R. Priya, "An Implementation Of Statistical Feature Algorithms For The Detection
Of Brain Tumor", Journal of Cognitive Human-Computer Interaction, 2021, DOI:
https://doi.org/10.54216/JCHCI.010202.
| Style | # |
|---|---|
| MLA | Rupesh Chaudhari, Ritik Gad, Pranav Gawali, Mangesh Gite, Dr. A. B. Pawa. "Hate Speech Detection on Social Media Using Machine Learning Algorithms." Journal of Cognitive Human-Computer Interaction, Vol. 2, No. 2, 2022 ,PP. 56-59 (Doi : https://doi.org/10.54216/JCHCI.020203) |
| APA | Rupesh Chaudhari, Ritik Gad, Pranav Gawali, Mangesh Gite, Dr. A. B. Pawa. (2022). Hate Speech Detection on Social Media Using Machine Learning Algorithms. Journal of Journal of Cognitive Human-Computer Interaction, 2 ( 2 ), 56-59 (Doi : https://doi.org/10.54216/JCHCI.020203) |
| Chicago | Rupesh Chaudhari, Ritik Gad, Pranav Gawali, Mangesh Gite, Dr. A. B. Pawa. "Hate Speech Detection on Social Media Using Machine Learning Algorithms." Journal of Journal of Cognitive Human-Computer Interaction, 2 no. 2 (2022): 56-59 (Doi : https://doi.org/10.54216/JCHCI.020203) |
| Harvard | Rupesh Chaudhari, Ritik Gad, Pranav Gawali, Mangesh Gite, Dr. A. B. Pawa. (2022). Hate Speech Detection on Social Media Using Machine Learning Algorithms. Journal of Journal of Cognitive Human-Computer Interaction, 2 ( 2 ), 56-59 (Doi : https://doi.org/10.54216/JCHCI.020203) |
| Vancouver | Rupesh Chaudhari, Ritik Gad, Pranav Gawali, Mangesh Gite, Dr. A. B. Pawa. Hate Speech Detection on Social Media Using Machine Learning Algorithms. Journal of Journal of Cognitive Human-Computer Interaction, (2022); 2 ( 2 ): 56-59 (Doi : https://doi.org/10.54216/JCHCI.020203) |
| IEEE | Rupesh Chaudhari, Ritik Gad, Pranav Gawali, Mangesh Gite, Dr. A. B. Pawa, Hate Speech Detection on Social Media Using Machine Learning Algorithms, Journal of Journal of Cognitive Human-Computer Interaction, Vol. 2 , No. 2 , (2022) : 56-59 (Doi : https://doi.org/10.54216/JCHCI.020203) |