References
[1]. Agarwal, A., Xie, B., Vovsha, I., Rambow, O., &
Passonneau, R. J. (2011, June). Sentiment analysis of
twitter data. In Proceedings of the Workshop on
Language in Social Media (LSM 2011) (pp. 30-38).
[2]. Carta, S., Corriga, A., Mulas, R., Recupero, D. R., &
Saia, R. (2019, September). A supervised multi-class multi-label word embeddings approach for toxic
comment classification. In 11th International Joint
Conference on Knowledge Discovery, Knowledge
Engineering and Knowledge Management (KDIR-2019)
(pp. 105-112). https://doi.org/10.5220/0008110901050112
[3]. Çiğdem, A. C. I., Çürük, E., & Eşsiz, E. S. (2019).
Automatic detection of cyberbullying in formspring. Me,
myspace and Youtube social networks. Turkish Journal of
Engineering, 3(4), 168-178. https://doi.org/10.31127/tuje.554417
[4]. d'Sa, A. G., Illina, I., & Fohr, D. (2019). Towards nontoxic
landscapes: Automatic toxic comment detection
using DNN. arXiv preprint arXiv:1911.08395. https://doi.org/10.48550/arXiv.1911.08395
[5]. Hosseini, H., Kannan, S., Zhang, B., & Poovendran, R.
(2017). Deceiving Google's perspective API built for
detecting toxic comments. arXiv preprint arXiv:1702.08138. https://doi.org/10.48550/arXiv.1702.08138
[6]. Li, S. (2018). Application of Recurrent Neural Networks
in Toxic Comment Classification (Doctoral dissertation,
UCLA).
[7]. Risch, J., Ruff, R., & Krestel, R. (2020). Explaining
offensive language detection. Journal for Language Technology and Computational Linguistics, 34(1), 29-47.
https://doi.org/10.21248/jlcl.34.2020.223
[8]. Sharma, R., & Patel, M. (2018). Toxic comment
classification using neural networks and machine
learning. International Advanced Research Journal in
Science, Engineering and Technology, 5(9), 47-52.
https://doi.org/10.17148/IARJSET.2018.597
[9]. Srivastava, S., Khurana, P., & Tewari, V. (2018, August).
Identifying aggression and toxicity in comments using
capsule network. In Proceedings of the First Workshop on
Trolling, Aggression and Cyberbullying (TRAC-2018) (pp.
98-105).
[10]. Van Aken, B., Risch, J., Krestel, R., & Löser, A. (2018).
Challenges for toxic comment classification: An in-depth
error analysis. arXiv preprint arXiv:1809.07572. https://doi.org/10.48550/arXiv.1809.07572
[11]. Yin, D., Xue, Z., Hong, L., Davison, B. D., Kontostathis,
A., & Edwards, L. (2009). Detection of harassment on web
2.0. Proceedings of the Content Analysis in the WEB, 2,
1-7.
[12]. Zaheri, S., Leath, J., & Stroud, D. (2020). Toxic
comment classification. SMU Data Science Review, 3(1),
1-16.