@article{f6fb314b9ec04ca89a1b2842e2a45111,
title = "Are vulnerable communities digitally left behind in social responses to natural disasters? An evidence from Hurricane Sandy with Twitter data",
abstract = "Social media data is increasingly being used to improve disaster resilience and response. Recent years have seen more efforts to integrate social media feeds with various demographic and socioeconomic variables to gain insight into the geographical and social disparities in social media use surrounding disasters. However, vulnerability concepts and indicators have been largely overlooked despite that they can offer aid in understanding and measuring the communities{\textquoteright} sensitivity to natural hazards and their capability of responding to and recovering from disasters. This study addresses a research question: Are vulnerable communities digitally left behind in social responses to natural disasters? Our empirical analysis is based on Hurricane Sandy and is conducted in a pre-disaster setting with spatial regression modeling. We observe that physically vulnerable communities had more intense social responses while socially vulnerable communities were digitally left behind in pre-disaster social responses to Hurricane Sandy.",
keywords = "Hurricane Sandy, Physical vulnerability, Social media, Social vulnerability, Twitter",
author = "Zheye Wang and Lam, {Nina S.N.} and Nick Obradovich and Xinyue Ye",
note = "Funding Information: This article is based on work supported by two research grants from the U.S. National Science Foundation: one under the SBE Office of Multidisciplinary Activities (SMA)organization in Interdisciplinary Behavioral and Social Science Research (IBSS)Program (Award No. 1620451), and the other under the NSF Social and Economic Sciences Division (SES)Hurricane Harvey 2017 Program (Award No. 1762600). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding agencies. Funding Information: This article is based on work supported by two research grants from the U.S. National Science Foundation : one under the SBE Office of Multidisciplinary Activities (SMA) organization in Interdisciplinary Behavioral and Social Science Research (IBSS) Program (Award No. 1620451 ), and the other under the NSF Social and Economic Sciences Division (SES) Hurricane Harvey 2017 Program (Award No. 1762600 ). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding agencies. Publisher Copyright: {\textcopyright} 2019 Elsevier Ltd",
year = "2019",
month = jul,
doi = "10.1016/j.apgeog.2019.05.001",
language = "English (US)",
volume = "108",
pages = "1--8",
journal = "Applied Geography",
issn = "0143-6228",
publisher = "Elsevier BV",
}