Machine Learning Approaches to Understanding the Psychological Impact of Cyberbullying on Adolescents

EasyChair Preprint 13730

Abstract

Cyberbullying has emerged as a significant societal concern, particularly its impact on adolescents' psychological well-being. This paper explores the application of machine learning approaches to understand the psychological impact of cyberbullying on adolescents. Machine learning techniques offer a promising avenue for analyzing large-scale data to uncover patterns and trends that may be indicative of psychological distress. By leveraging machine learning algorithms, researchers can extract valuable insights from diverse data sources such as social media, online forums, and surveys. This abstract provides an overview of the potential of machine learning in elucidating the complex relationship between cyberbullying and psychological outcomes in adolescents.

Keyphrases: Cyberbullying, machine learning, psychological outcomes in adolescents.

@booklet{EasyChair:13730,
  author    = {Abi Cit and Zakarya Jahin and Zakarya Jesan},
  title     = {Machine Learning Approaches to Understanding the Psychological Impact of Cyberbullying on Adolescents},
  howpublished = {EasyChair Preprint 13730},
  year      = {EasyChair, 2024}}