Citation

Leykin D, Lahad M, Aharonson-Daniel L. Int. J. Disaster Risk Reduct. 2018; 31: 393-402.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.ijdrr.2018.04.021

PMID

unavailable

Abstract

Resilience is a broad concept that encompasses different kinds of phenomena, such as effective functioning under severe conditions, adaptation to stress and attaining normal functioning after exposure to potentially traumatic experiences. The study of resilient behavior of individuals, communities and societies provide researchers and practitioners with better knowledge and understanding of human coping and adaptation. Reports about unfortunate and stressful events in social media news sites trigger various appraisals among social media users. Some of these appraisals are translated into user generated symbolic, textual and visual content - and offer a unique opportunity to observe how the public "digests" and copes with the changing reality. With the rise of social media, the abundance of user-generated content, public application programming interfaces for social media services and the availability of efficient data extraction and analytical tools - researchers and practitioners can explore in detail citizen' attitudes towards various issues in their external environment, including in-depth understanding of their coping modes and resiliency. The objective of this review is to describe how existing and recently developed tools in the field of social computing can be utilized to assess different aspects of resilience, through mining of the social media. We propose several indicators for resilience factors, and present methods and techniques to search, processes and analyze textual and visual content, commonly published on social media. It is proposed that automatic and immediate detection of resilience factors in users' discourse, will significantly improve the ability of decision makers generate public situational awareness based on social media data.

Language: en