In the 108th episode of the Behind the Science podcast series, Engineer Raymond “Pam” Lagria highlights how the digital revolution, particularly the rise of social media, is shaping more responsive disaster management systems. Through his research in Industrial Engineering, social media posts such as “tweets” (now X) are analyzed to identify and prioritize urgent calls for help, enabling faster and more targeted disaster response while supporting broader efforts in risk reduction, prevention, and mitigation.
Industrial engineering has extended its applications beyond healthcare and business operations. To date, it has evolved into a tool for improving disaster response across sectors and communities. According to Mr. Lagria, the role of industrial engineers has focused on enhancing efficiency and decision-making through systems thinking and data-driven approaches.
Based on the text mining framework developed in his research, disaster-related social media posts can be classified and ranked according to urgency using a scoring system and keyword-based analysis, helping identify which content requires immediate attention. This development forms part of a broader system aimed at supporting disaster responders through real-time situational awareness. His research also highlights social media as one of the primary platforms Filipinos turn to during events such as earthquakes and typhoons, offering valuable insights into real-time and lived experiences that can inform disaster response efforts.
Inspired by his experiences during Typhoon Yolanda in 2013, Mr. Lagria recognized the potential of his field to contribute to disaster risk reduction and management. As industrial engineering continues to highlight the importance of data mining, research methodologies, and data-driven decision-making in DRRM, he encourages aspiring researchers to remain open-minded and willing to learn, embracing the rigorous process of trial and error. Innovations such as social media-based analytics demonstrate the growing potential of community-based data mining in strengthening disaster resilience, particularly in hazard-prone countries like the Philippines.
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Research spotlight:
Lagria, R., et. al. “A Text Mining Framework for the Classification and Prioritization of Disaster-Related Tweets for Disaster Response”. Philippine Engineering Journal 2022 Vol. 43, No.: 65-88
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