Abstract
Emotions are not linguistic entities, although they are easily articulated through language. Emotions influence our actions, ideas, and, of course, how we communicate. On the other hand, abusive text, such as undiscriminating slang, offensive language, and vulgarity, is more than just a message; it is a tool for very serious and brutal cyber violence. Hence, detection of such language has become very important in any language now-a-days. Therefore, many works and researches have been done on detecting emotional language, abusive language or both in many dialects including Bangla. This paper proposes to present a comparative analysis of different researches made on detecting emotional and abusive Bangla language. It further aims to present the best approach that tailors certain attributes of emotional and abusive language detection with respect to their prognosis performance and their implementation toughness in Bangla lingo. Potential enhancements for future study are presented in the paper, while the limitations of current researches are addressed and discussed. This work seeks to bring a fresh viewpoint to the joint modeling of emotional and abusive language detection in Bangla by examining and criticizing flaws and in order to offer future changes, poor design choices must be examined.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Buz, T.: Comparative analysis of neural NLP models for information extraction from accounting documents. Ph.D. thesis, ETSI_Informatica (2018)
Johri, P., Khatri, S.K., Al-Taani, A.T., Sabharwal, M., Suvanov, S., Kumar, A.: Natural language processing: history, evolution, application, and future work. In: Abraham, A., Castillo, O., Virmani, D. (eds.) Proceedings of 3rd International Conference on Computing Informatics and Networks. LNNS, vol. 167, pp. 365–375. Springer, Singapore (2021). https://doi.org/10.1007/978-981-15-9712-1_31
Nadkarni, P.M., Ohno-Machado, L., Chapman, W.W.: Natural language processing: an introduction. J. Am. Med. Inform. Assoc. 18(5), 544–551 (2011)
Cambria, E., White, B.: Jumping NLP curves: a review of natural language processing research. IEEE Comput. Intell. Mag. 9(2), 48–57 (2014)
Munro, E.R.: The protection of children online: a brief scoping review to identify vulnerable groups. Childhood Wellbeing Research Centre (2011)
Hassan, F.M., Khalifa, F.N., El Desouky, E.D., Salem, M.R., Ali, M.M.: Cyber violence pattern and related factors: online survey of females in Egypt. Egypt. J. Forensic Sci. 10(1), 1–7 (2020)
Rajamanickam, S., Mishra, P., Yannakoudakis, H., Shutova, E.: Joint modelling of emotion and abusive language detection. arXiv preprint arXiv:2005.14028 (2020)
Bagga, S.: Detecting Abuse on the Internet: It’s Subtle. McGill University (Canada) (2020)
Duggan, M.: Online harassment 2017 (2017)
Stone, L.: Emotional Language in Literature - Writing Review (Video) – mometrix.com. https://www.mometrix.com/academy/express-feelings/. Accessed 05 Apr 2022
Murthy, A.R., Anil Kumar, K.M.: A review of different approaches for detecting emotion from text. In: IOP Conference Series: Materials Science and Engineering, vol. 1110, p. 012009. IOP Publishing (2021)
Islam, M.S.: Research on Bangla language processing in Bangladesh: progress and challenges. In: 8th International Language and Development Conference, pp. 23–25 (2009)
Mehedy, L., Arifin, N., Kaykobad, M.: Bangla syntax analysis: a comprehensive approach. In: Proceedings of International Conference on Computer and Information Technology (ICCIT), Dhaka, Bangladesh, pp. 287–293 (2003)
Emon, E.A., Rahman, S., Banarjee, J., Das, A.K., Mittra, T.: A deep learning approach to detect abusive Bengali text. In: 2019 7th International Conference on Smart Computing and Communications (ICSCC), pp. 1–5. IEEE (2019)
Chakraborty, P., Seddiqui, M.H.: Threat and abusive language detection on social media in Bengali language. In: 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT), pp. 1–6. IEEE (2019)
Rabeya, T., Ferdous, S., Ali, H.S., Chakraborty, N.R.: A survey on emotion detection: a lexicon based backtracking approach for detecting emotion from Bengali text. In: 2017 20th International Conference of Computer and Information Technology (ICCIT), pp. 1–7. IEEE (2017)
Rayhan, M.M., Al Musabe, T., Islam, M.A.: Multilabel emotion detection from Bangla text using BiGRU and CNN-BiLSTM. In: 2020 23rd International Conference on Computer and Information Technology (ICCIT), pp. 1–6. IEEE (2020)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Rahman, A.I. et al. (2022). Comparative Analysis on Joint Modeling of Emotion and Abuse Detection in Bangla Language. In: Singh, M., Tyagi, V., Gupta, P.K., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2022. Communications in Computer and Information Science, vol 1614. Springer, Cham. https://doi.org/10.1007/978-3-031-12641-3_17
Download citation
DOI: https://doi.org/10.1007/978-3-031-12641-3_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-12640-6
Online ISBN: 978-3-031-12641-3
eBook Packages: Computer ScienceComputer Science (R0)