Role of Large-Scale Data Analytics Risk Information Systems in Addressing Social Disruptions in Infrastructure Development

Rafadi Khan Khayru (Universitas Sunan Giri Surabaya)
Khowanas Saeed Qader (College of Administration and Economics, Lebanese French University, Kurdistan Region, Erbil, Iraq)

Bulletin of Science, Technology and Society
Vol 5 No 2 (2026): Bulletin of Science, Technology and Society (August)

Large-scale public infrastructure development frequently triggers social conflicts due to delayed identification of community concerns. This study aims to analyze and evaluate the effectiveness of a Big Data-based risk management information system in mitigating social conflicts in public infrastructure projects. Utilizing a qualitative approach with a case study design, data were collected through in-depth interviews, observations, and system log document analysis. The findings indicate that digital data processing integrating natural language processing and social media sentiment analysis provides accurate early warnings regarding conflict-prone zones. The rapid field intervention driven by precise data predictions successfully reduced project disruption incidents and enhanced public trust. This study concludes that the effectiveness of social risk management is fundamentally determined by the synergy between smart data analytics, inter-agency coordination, and humanistic communication actions.