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The 2030 Global Sustainable Development Agenda of United Nations highlighted the critical importance of understanding the integrated nature between enhancing infrastructure resilience and facilitating social equity. Social equity is defined as equal opportunities provided to different people by infrastructure. It addresses disparities and unequal distribution of goods, services, and amenities. Infrastructure resilience is defined as the ability of infrastructure to withstand, adapt, and quickly recover from disasters. Existing research shows that infrastructure resilience and social equity are closely related to each other. However, there is a lack of research that explicitly understands the complex relationships between infrastructure resilience and social equity. To address this gap, this study aims to examine such interrelationships using social media data. Social media data is increasingly being used by researchers and proven to be a reliable source of valuable information for understanding human activities and behaviors in a disaster setting. The spatiotemporal distribution of disaster-related messages helps with real-time and quick assessment of the impact of disasters on infrastructure and human society across different regions. Using social media data also offers the advantages of saving time and cost, compared to other traditional data collection methods. As a first step of this study, this paper presents our work on collecting and analyzing the Twitter activities during 2018 Hurricane Michael in disaster-affected counties of Florida Panhandle area. The collected Twitter data was organized based on the geolocations of affected counties and was compared against the infrastructure resilience and social equity data of the affected counties. The results of the analysis indicate that (1) Twitter activities can be used as an important indicator of infrastructure resilience conditions, (2) socially vulnerable populations are not as active as general populations on social media in a disaster setting, and (3) vulnerable populations require a longer time for disaster recovery.
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Improve disaster communication in hyperlocal online and offline communities using social media data: A case study of the 2015 Nepal earthquake.
This article seeks to go beyond traditional GIS methods used in creating maps for disaster response that commonly look at the disaster extent. Instead, a slightly different approach is taken using social media data collected from Twitter to explore how people communicate during disaster events, how online communities form and evolve, and how communication methods can improve. This study collected the Twitter data during the 2015 Nepal earthquake disaster and applied a spatiotemporal analysis to find any patterns that show shadows or gaps in communication channels in local communities’ communication. Linkages in social media can be used to understand how people communicate, how quickly they diffuse information, and how social networks form online during disasters. These can improve communication throughout disaster phases. This study offers a deeper understanding of the kinds of spatiotemporal patterns and spatial social networks that can be observed during disaster events. The need for better communication during disaster events is imperative for better disaster management, increasing community resilience, and saving lives.
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- Award ID(s):
- 1634641
- PAR ID:
- 10108845
- Date Published:
- Journal Name:
- Proceedings in 2019 Annual Meeting of Transportation Research Board (TRB), January 13–17, Washington D.C.
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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