Machine Learning Methods for detection of bystanders: A Survey

The number of users on social media networks is increasing day by day as their popularity increases. The users are sharing their photos, videos, daily life, experiences, views, and status updates on different social networking sites. Social networking sites give great possibilities for young people to interact with others, but they also make them more subject to unpleasant phenomena such as online harassment and abusive language, which leads to cyberbullying. Cyberbullying is a prevalent social problem that inflicts detrimental consequences to the health and safety of victims such as psychological distress, anti-social behavior, and suicide. To minimize the impact of Cyberbullying, the Bystander role is very important. In this paper, a review of the cyberbullying content on the Internet, the classification of cyberbullying categories, classifying author roles (harasser, victim, bystander-defender, bystander-assistant), data sources containing cyberbullying data for research, and machine learning techniques for cyberbullying detection are overviewed.&nbsp

Abstracts of Scientifica 2022

This book contains the abstracts of the papers presented at Scientifica 2022, Organized by the Sancheti Institute College of Physiotherapy, Pune, Maharashtra, India, held on 12–13 March 2022. This conference helps bring researchers together across the globe on one platform to help benefit the young researchers. There were six invited talks from different fields of Physiotherapy and seven panel discussions including over thirty speakers across the globe which made the conference interesting due to the diversity of topics covered during the conference. Conference Title:  Scientifica 2022Conference Date: 12–13 March 2022Conference Location: Sancheti Institute College of PhysiotherapyConference Organizer: Sancheti Institute College of Physiotherapy, Pune, Maharashtra, Indi