Semantics-enriched spatiotemporal mapping of public risk perceptions for cultural heritage during radical events

A study reveals distinct spatiotemporal patterns of public risk perceptions on social media during Heritage-Related Events (HREs), using the 2019 Notre Dame fire and Venice flood as case studies. Analysis of Twitter data shows heightened online activity and emotional responses before, during, and after these events, with machine learning models identifying dominant topics and sentiments. The research highlights how public reactions vary based on event severity, offering insights for urban risk reduction and heritage management. This methodological framework also advances Geo-AI applications in spatiotemporal clustering.

Bai, N., Nourian, P., Cheng, T., & Pereira Roders, A. (2024). Semantics-enriched spatiotemporal mapping of public risk perceptions for cultural heritage during radical events. International Journal of Disaster Risk Reduction, 113, 104857. https://doi.org/10.1016/j.ijdrr.2024.104857