Understanding Adolescent Online Sexual Patterns Through Big Data Analysis - Yusman, Yanti; Mohd Noor, Noor Anida Zaria (Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies, 2025)
The rapid growth of digital technology and the increasing use of social media among adolescents in Indonesia, particularly in Padang, West Sumatra, have raised concerns about online sexual risk behaviors such as sexting, sharing explicit content, and unsafe interactions with strangers. Previous studies in Indonesia have largely relied on small- scale surveys, which are insufficient to capture the complex and dynamic nature of adolescents’ digital behaviors. This study aims to understand patterns of online sexual risk behaviors among adolescents in Padang through a big data analysis approach. Data were collected from popular social media platforms frequently used by teenagers and processed using text mining, natural language processing (NLP), and sentiment analysis. Clustering techniques and social network analysis were applied to identify behavioral patterns, interaction dynamics, and vulnerable groups. The findings reveal diverse patterns of behavior, ranging from curiosity-driven exploration to high-risk involvement influenced by peer pressure and exposure to sexual content online. Network analysis further indicates that digital communities play a significant role in shaping adolescents’ risky sexual behaviors in Padang. This study demonstrates that big data analytics provide a more comprehensive understanding compared to traditional survey methods, and highlights important implications for sexual health education, digital parenting strategies, and child protection policies at both local and national levels.