Socialmedia such as Twitter is increasingly beingused as an effective platform to observe human behaviors in disastrous events.However,uneven social media use among different groups of population in different regions ...Socialmedia such as Twitter is increasingly beingused as an effective platform to observe human behaviors in disastrous events.However,uneven social media use among different groups of population in different regions could lead to biased consequences and affect disaster resilience.This paper studies the Twitter use during 2017 Hurricane Harvey in 76 counties in Texas and Louisiana.We seek to answer a fundamental question:did socialgeographical disparities of Twitter use exist during the three phases of emergency management(preparedness,response,recovery)?We employed a Twitter data mining framework to process the data and calculate two indexes:Ratio and Sentiment.Regression analyses between the Ratio indexes and the social-geographical characteristics of the counties at the three phrases reveal significant social and geographical disparities in Twitter use during Hurricane Harvey.Communities with higher disasterrelated Twitter use in Harvey generally were communities having better social and geographical conditions.These results of Twitter use patterns can be used to compare with future similar studies to see whether the Twitter use disparities have increased or decreased.Future research is also needed to examine the effects of Twitter use disparities on disaster resilience and to test whether Twitter use can predict community resilience.展开更多
基金the SBE Office of Multidisciplinary Activities(SMA)organization in Interdisciplinary Behavioral and Social Science Research(IBSS)Program(Award No.1620451)the NSF Social and Economic Sciences Division(SES)Hurricane Harvey 2017 Program(Award No.1762600)。
文摘Socialmedia such as Twitter is increasingly beingused as an effective platform to observe human behaviors in disastrous events.However,uneven social media use among different groups of population in different regions could lead to biased consequences and affect disaster resilience.This paper studies the Twitter use during 2017 Hurricane Harvey in 76 counties in Texas and Louisiana.We seek to answer a fundamental question:did socialgeographical disparities of Twitter use exist during the three phases of emergency management(preparedness,response,recovery)?We employed a Twitter data mining framework to process the data and calculate two indexes:Ratio and Sentiment.Regression analyses between the Ratio indexes and the social-geographical characteristics of the counties at the three phrases reveal significant social and geographical disparities in Twitter use during Hurricane Harvey.Communities with higher disasterrelated Twitter use in Harvey generally were communities having better social and geographical conditions.These results of Twitter use patterns can be used to compare with future similar studies to see whether the Twitter use disparities have increased or decreased.Future research is also needed to examine the effects of Twitter use disparities on disaster resilience and to test whether Twitter use can predict community resilience.
