Cyberbullying-Mediated Depression Detection in Social Media Using Machine Learning
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Publisher
Springer Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-16-3346-1_70
Reference20 articles.
1. Depression-World Health Organization. https://www.who.int/news-room/fact-sheets/detail/depression
2. Viner, R. M., Aswathikutty-Gireesh, A., Stiglic, N., Hudson, L. D., Goddings, A.-L., Ward, J. L., & Nicholls, D. E.: Roles of cyberbullying, sleep and physical activity in mediating the effects of social media use on mental health and wellbeing among young people in England: A secondary analysis of longitudinal data. Journal of The Lancet Child and Adolescent Health, 3(10), 685–696 (2019). https://doi.org/10.1016/s2352-4642(19)30186-5
3. Kumar, A., & Sachdeva, N. (2020) Cyberbullying checker: Online bully content detection using hybrid supervised learning. In International Conference on Intelligent Computing and Smart Communication 2019 (pp. 371–382). Springer, Singapore.
4. Kumar, A., & Sachdeva, N. (2020) Multi-input integrative learning using deep neural networks and transfer learning for cyberbullying detection in real-time code-mix data. Journal of Multimedia Systems, 66. https://doi.org/10.1007/s00530-020-00672-7
5. Kumar, A., & Sachdeva, N. (2019). Cyberbullying detection on social multimedia using soft computing techniques: A meta-analysis. Journal Multimedia Tools Appl, 78, 23973–24010. https://doi.org/10.1007/s11042-019-7234-z
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