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Books > Business & Economics > Economics > Econometrics
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Social Media Communication Data for Recovery - Detecting Socio-Economic Activities Following a Disaster (Hardcover, 1st ed. 2020)
Loot Price: R3,627
Discovery Miles 36 270
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Social Media Communication Data for Recovery - Detecting Socio-Economic Activities Following a Disaster (Hardcover, 1st ed. 2020)
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This book explores the possibility of using social media data for
detecting socio-economic recovery activities. In the last decade,
there have been intensive research activities focusing on social
media during and after disasters. This approach, which views
people's communication on social media as a sensor for real-time
situations, has been widely adopted as the "people as sensor"
approach. Furthermore, to improve recovery efforts after
large-scale disasters, detecting communities' real-time recovery
situations is essential, since conventional socio-economic recovery
indicators, such as governmental statistics, are not published in
real time. Thanks to its timeliness, using social media data can
fill the gap. Motivated by this possibility, this book especially
focuses on the relationships between people's communication on
Twitter and Facebook pages, and socio-economic recovery activities
as reflected in the used-car market data and the housing market
data in the case of two major disasters: the Great East Japan
Earthquake and Tsunami of 2011 and Hurricane Sandy in 2012. The
book pursues an interdisciplinary approach, combining e.g. disaster
recovery studies, crisis informatics, and economics. In terms of
its contributions, firstly, the book sheds light on the "people as
sensors" approach for detecting socio-economic recovery activities,
which has not been thoroughly studied to date but has the potential
to improve situation awareness during the recovery phase. Secondly,
the book proposes new socio-economic recovery indicators: used-car
market data and housing market data. Thirdly, in the context of
using social media during the recovery phase, the results
demonstrate the importance of distinguishing between social media
data posted both by people who are at or near disaster-stricken
areas and by those who are farther away.
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