Machine Learning in Social Sciences Exploring Innovations and Ethical Challenges

Abstract

Bullying is an important issue in higher education, with heavy consequences for student's mental health. Machine learning (ML) has transformed the research landscape across diverse fields, including the social sciences. Its ability to analyze vast datasets and identify complex patterns has led to revolutionary advancements in understanding human behavior, societal trends, and policy-making. This paper provides a comprehensive overview of ML applications in social sciences, discussing key methodologies, results from recent studies, and emerging challenges. We highlight case studies where ML tools have successfully predicted social phenomena and analyzed large datasets, offering insights into socioeconomic, political, and cultural dimensions.