SOCIAL MEDIA USAGE PATTERNS AND EMOTIONAL WELL-BEING: A CROSS-PLATFORM ANALYSIS OF DIGITAL HUMAN BEHAVIOR

Abstract

Culture is not the sole determinant of human prejudice and democratic quality; it is a product of interactions among ecological pressures, developmental conditions, and institutional environments. This study examines these dynamics from a cross-national social–ecologiThis study examines the relationship between social media usage patterns and emotional well-being through a cross-platform analytical perspective. It seeks to learn the effects of various aspects of digital interactions on how users emotionally experience them. The research design used was a quantitative, cross-sectional study that relied on a secondary dataset that was acquired through Kaggle. A total of 1000 observations in the dataset were pre-processed to yield 924 valid cases. The analysis of the study was done with Python and included descriptive statistics, correlation, and classification modeling to analyze the relationships between usage behaviors and prevailing emotional states. The findings show that there is high social media usage, and the Instagram platform has been identified as the most widely used. Emotional outcomes were diverse, with happiness and neutrality being the most prevalent, alongside notable levels of anxiety and sadness. Strong positive correlations were observed between usage intensity and engagement metrics. The classification model demonstrated moderate predictive capability uggesting that behavioral patterns can partially explain emotional outcomes. The findings highlight the complex and dual nature of social media, acting as both a source of social connection and emotional strain. The study contributes to understanding digital human behavior and offers insights for developing strategies to promote health healthier online engagement.