Assessment of Post-Disaster Concerns using Social Network Analysis and Machine Learning: A Study of 2018 Palu Disaster

Abstract

Post-disaster needs assessment plays a critical role in developing emergency response programs and disaster preparedness. An assessment of needs identifies possible interventions or assistance and the necessary resources for emergency responses. This emergency need assessment assists stakeholders in defining possible response options, evaluating the priorities of needs of affected communities, and determining what support will be required immediately. The prevalent use of social media in Indonesia highlights its significance as a crucial means of acquiring prompt, effortless, individualized, and geo-specific information regarding the demands and requirements of communities impacted by a calamity. This study aims to analyze the tweets posted by local communities affected by the 2018 Central Sulawesi earthquakes, tsunami, and liquefaction using the Social Network Analysis (SNA) method based on machine learning and natural language processing. Through this analysis, we intend to observe the spatial interaction and relationship among the affected areas of communities for the needs and concerns after the disaster to enhance the relief operation. We found that social media users, government, and humanitarian organizations effectively shared information during the disaster. This study also underlined that the behavioral responses of individuals to disasters were not limited to the disaster-stricken areas but extended far beyond them. This action suggests that they were willing to exhibit a more empathetic, benevolent, and philanthropic demeanor in the face of such traumatic events.

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