Mapping the Landscape: A Comprehension Review of Automated Cyberbullying Detection in Digital World
Nidhi Nigam, Poorva Shukla, Namrata Nebhnani · Advances in intelligent systems research/Advances in Intelligent Systems Research · 2025
Digital world provides platforms to people at large scale to share their updates, opinions publically.Various social media platforms, online messaging forums and applications are channels to spread digital hate through Cyberbullying, hate speech etc. in native languages.Cyberbullying detection is one of most crucial action to be taken for safeguarding for individuals, organizations with the intention to promote digital safety by following ethical norms.It is important to address the consequences of such actions by implementing fool proof efficient and effective measures.In order to promote digital hygiene and as solutions of the issues technology integration plays vital role.This paper covers the review of automated cyberbullying detection methods using different domains like machine learning, Natural Language Processing, Generative Artificial Intelligence and more.Study of numerous approaches applying datasets from different social media platforms is systematically analysed.Additionally comparative studies between identified parameters with their results are investigated.In summary issues and challenges for cyberbullying detection system are identified which will help to promote healthy digital environment and society.