Detection of Social Media Cyberbullying in the Bengali Language : A Comparative Study

Prangon, S.A.M Sajratul Yeaken Mollah; Asif, Anik Emtiaz; Taha, Fayeaz-E-Abrar

dc.contributor.author	Prangon, S.A.M Sajratul Yeaken Mollah
dc.contributor.author	Asif, Anik Emtiaz
dc.contributor.author	Taha, Fayeaz-E-Abrar
dc.date.accessioned	2025-06-03T06:26:12Z
dc.date.available	2025-06-03T06:26:12Z
dc.date.issued	2024-06-30
dc.identifier.citation	[1] A. Akrim, “Student perception of cyberbullying in social media,” Aksaqila Jab fung, 2022. [2] T. T. Aurpa, R. Sadik, and M. S. Ahmed, “Abusive bangla comments detection on facebook using transformer-based deep learning models,” Social Network Analysis and Mining, vol. 12, no. 1, p. 24, 2022. [3] S. Batool, R. Yousaf, and F. Batool, “Bullying in social media: An effect study of cyber bullying on the youth,” Pakistan Journal of Criminology, vol. 9, no. 4, p. 119, 2017. [4] A. Bozyiğit, S. Utku, and E. Nasibov, “Cyberbullying detection: Utilizing social media features,” Expert Systems with Applications, vol. 179, p. 115 001, 2021. [5] E. Byrne, J. A. Vessey, and L. Pfeifer, “Cyberbullying and social media: Infor mation and interventions for school nurses working with victims, students, and families,” The Journal of School Nursing, vol. 34, no. 1, pp. 38–50, 2018. [6] M. A. Carter, “Protecting oneself from cyber bullying on social media sites– a study of undergraduate students,” Procedia-Social and Behavioral Sciences, vol. 93, pp. 1229–1235, 2013. [7] B. R. Chakravarthi, “Multilingual hope speech detection in english and dra vidian languages,” International Journal of Data Science and Analytics, vol. 14, no. 4, pp. 389–406, 2022. [8] D. Chatzakou, I. Leontiadis, J. Blackburn, et al., “Detecting cyberbullying and cyberaggression in social media,”ACM Transactions on theWeb (TWEB), vol. 13, no. 3, pp. 1–51, 2019. [9] R. R. Dalvi, S. B. Chavan, and A. Halbe, “Detecting a twitter cyberbullying using machine learning,” in 2020 4th International Conference on Intelligent Comput ing and Control Systems (ICICCS), IEEE, 2020, pp. 297–301. [10] M. I. H. Emon, K. N. Iqbal, M. H. K. Mehedi, M. J. A. Mahbub, and A. A. Rasel, “Detection of bangla hate comments and cyberbullying in social media using 24 nlp and transformer models,” in International Conference on Advances in Com puting and Data Sciences, Springer, 2022, pp. 86–96. [11] A. Görzig and L. A. Frumkin, “Cyberbullying experiences on-the-go: When so cial media can become distressing,” Cyberpsychology: Journal of Psychosocial Research on Cyberspace, vol. 7, no. 1, 2013. [12] F. Hassan, M. R. A. Kotwal, and M. N. Huda, “Bangla asr design by suppressing gender factor with gender-independent and gender-based hmm classifiers,” in 2011 World Congress on Information and Communication Technologies, 2011, pp. 1276–1281. doi: 10.1109/WICT.2011.6141432. [13] A. Ishmam and S. Sharmin, “Hateful speech detection in public facebook pages for the bengali language,” Dec. 2019, pp. 555–560. doi: 10.1109/ICMLA.2019. 00104. [14] H. Kelejian, “A spatial j-test for model specification against a single or a set of non-nested alternatives,”AStAWirtschafts- und Sozialstatistisches Archiv, vol. 1, pp. 3–11, Feb. 2008. doi: 10.1007/s12076-008-0001-9. [15] M. Kowsher, A. A. Sami, N. J. Prottasha, M. S. Arefin, P. K. Dhar, and T. Koshiba, “Bangla-bert: Transformer-based efficient model for transfer learning and lan guage understanding,” IEEE Access, vol. 10, pp. 91 855–91 870, 2022. doi: 10. 1109/ACCESS.2022.3197662. [16] H. Shahgir and K. Sayeed, Bangla grammatical error detection using t5 trans former model, Preprint available on arXiv, Mar. 2023. doi: 10.48550/arXiv. 2303.10612. arXiv: 2303.10612 [cs.CL]. [17] S. Singh, V. Thapar, and S. Bagga, “Exploring the hidden patterns of cyberbully ing on social media,” Procedia Computer Science, vol. 167, pp. 1636–1647, 2020. [18] M. Yao, C. Chelmis, and D.-S. Zois, “Cyberbullying ends here: Towards robust detection of cyberbullying in social media,” in The World Wide Web Conference, 2019, pp. 3427–3433. [19] M. T. Zaman, M. Zaman, F. Shah, and E. Ahmed, A deep learning-based bengali visual question answering system using contrastive loss, Available at Research Gate, Apr. 2024. doi: 10.13140/RG.2.2.32405	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/2416
dc.description	Supervised by Mr. Faisal Hasan, Assistant Professor, Department of Computer Science and Engineering (CSE) Islamic University of Technology (IUT) Board Bazar, Gazipur, Bangladesh This thesis is submitted in partial fulfillment of the requirement for the degree of Bachelor of Science in Software Engineering, 2024	en_US
dc.description.abstract	As social media platforms have become more widely used, cyberbullying has become a major issue that cuts over linguistic and geographic barriers. Although significant efforts have been made to identify cyberbullying in major languages, little research has been done in this area regarding Bengali, despite its distinctive linguistic charac teristics. An automated method for identifying instances of cyberbullying in Bengali social media content is presented in this thesis. This study examines of current cyberbullying detection techniques and how well they work in the context of Bengali language usage.Our study includes feature extraction, classification, and data preprocessing, all of which are optimized to take into account the nuances of the Bengali language. Important language elements that are typical of Bengali cyberbullying discourse are found and added to the feature extraction procedure. Additionally, semi-supervised learning approaches are used to improve classification performance by utilizing both labeled and unlabeled data in order to offset the lack of labeled datasets in Bengali. Many experiments on real-world Bengali social media datasets are used to assess the efficacy of the suggested approach. performance metrics are compared amongst cur rent approaches in terms of F1-score metrics, precision, and recall	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Computer Science and Engineering(CSE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh	en_US
dc.title	Detection of Social Media Cyberbullying in the Bengali Language : A Comparative Study	en_US
dc.type	Thesis	en_US