Abstract
Social media is a platform for sharing content and interacting with other people through multimedia data such as photos, videos, and documents accessed via computers or smartphones. One of the most dangerous consequences of social media is the rise of cyberbullying, which is more diabolical than traditional bullying and hard to control. The objective of the system is to determine the bully score of the users, and it helps to identify how much the person is using bully phrases in social media. The proposed work aims to recognize the cyberbullying phrase in a tweet using VADER sentimental analysis of the user. BERT model is used to classify the bully tweets which performs with a better accuracy of 0.9535. A conversation graph is constructed by a bully score of each user with the help of the PageRank algorithm to identify the cyberbullies.
D. Manikandan, G. S. Nithish Kumar, M. Keerthika, B. Kavin are contributed equally to this work.
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Acknowledgements
This publication is an outcome of the Research and Development work undertaken in the project under SERB-POWER (Promoting Opportunities for Women in Exploratory Research) Fellowship, Science and Engineering Research Board, Department of Science and Technology, Government of India (File No. SPF/2021/000068).
Code of Interest No potential conflict of interest is reported by the authors.
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Valliyammai, C., Manikandan, D., Nithish Kumar, G.S., Keerthika, M., Kavin, B. (2024). Conversation Graph Construction Approach of Cyberbully Detection Using Bully Scores. In: Joshi, A., Mahmud, M., Ragel, R.G., Karthik, S. (eds) ICT: Innovation and Computing. ICTCS 2023. Lecture Notes in Networks and Systems, vol 879. Springer, Singapore. https://doi.org/10.1007/978-981-99-9486-1_35
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DOI: https://doi.org/10.1007/978-981-99-9486-1_35
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