Computational Social Science of Disasters: Opportunities and Challenges

Abstract

Disaster events and their economic impacts are trending, and climate projection studies suggest that the risks of disaster will continue to increase in the near future. Despite the broad and increasing social effects of these events, the empirical basis of disaster research is often weak, partially due to the natural paucity of observed data. At the same time, some of the early research regarding social responses to disasters have become outdated as social, cultural, and political norms have changed. The digital revolution, the open data trend, and the advancements in data science provide new opportunities for social science disaster research. We introduce the term computational social science of disasters (CSSD), which can be formally defined as the systematic study of the social behavioral dynamics of disasters utilizing computational methods. In this paper, we discuss and showcase the opportunities and the challenges in this new approach to disaster research. Following a brief review of the fields that relate to CSSD, namely traditional social sciences of disasters, computational social science, and crisis informatics, we examine how advances in Internet technologies offer a new lens through which to study disasters. By identifying gaps in the literature, we show how this new field could address ways to advance our understanding of the social and behavioral aspects of disasters in a digitally connected world. In doing so, our goal is to bridge the gap between data science and the social sciences of disasters in rapidly changing environments.

Implication of Mutual Assistance Evacuation Model to Reduce the Volcanic Risk for Vulnerable Society: Insight from Mount Merapi, Indonesia

“…The CSSD provides new theoretical grounds to investigate the complexities and the interacting processes involving traditional social sciences of disasters, computational social science, and crisis informatics. However, there is still a challenge in the collection and handling of human subject data [19]. Hawe et al revealed that Agent-based simulations (ABS) have become the de-facto technique for determining the best way to respond to a large-scale emergency.…”

Evaluation of TSP for Emergency Routing

“…Be it pandemic or disasters, it is predicted to continue and having a great impact on the socio-economic welfare of the entire world [1]. Authorities of emergency management service use several Emergency Response Computational Tool and Models (ERT) to route resources; however, advantages and limitations of such tools is not always clear [2].…”

About Linda Again: How Narratives and Group Reasoning Can Influence Conjunction Fallacy

“…Within the internet science community, there had been many efforts to improve collective decision-making by means of specific technologies [1][2][3][4]. For example, understanding how people reason (and, eventually, commit mistakes) at individual level or in group is crucial to improve the design of online crowdsourcing systems and software [5,6]. In this paper, we investigate a paradigmatic reasoning error, the conjunction fallacy.…”