A Review of the Past Decade's Research Outcomes on Classifying Cyberbullying
DOI:
https://doi.org/10.22401/6bg6p723Keywords:
Cyberbullying , Deep learning , Machine learning , Social media , Word EmbeddingAbstract
Cyberbullying is a new form of online violence that has emerged as a result of the social media industry's explosive expansion since it allows for indirect communication. Despite the usefulness of digital media, it has been used by weak people to threaten and bully others online. In the last ten years, research has shown that children and teenagers are increasingly experiencing cyberbullying as a concern. This paper examines the research conducted during the previous ten years, categorizes it, and presents statistical analyses of the data collected during that time. A table is used to present various data, including the dataset that was used, its size (number of samples, posts, or messages), the methods that were employed, and the metrics that were gathered from the examined research that was taken from the publications that were looked into. This survey will be helpful to everyone who wants to advance their understanding of how machine learning may be used to identify cyberbullying, and it may help create a social media environment that is safe and relatively healthy by automatically identifying bullying communications.
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