東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Social media communication data for ...

Shibuya, Yuya.

FindBook

Google Book

Amazon

博客來

Social media communication data for recovery = detecting socio-economic activities following a disaster /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Social media communication data for recovery/ by Yuya Shibuya.
其他題名:	detecting socio-economic activities following a disaster /
作者:	Shibuya, Yuya.
出版者:	Singapore :Springer Singapore : : 2020.,
面頁冊數:	xiii, 228 p. :ill., digital ;24 cm.
內容註:	Declaration of Authorship -- Abstract -- Acknowledgements -- Introduction and Framework Introduction -- Concept of "People as Sensors" -- Methodology -- Empirical Studies of Socio-Economic Activities After the Great East Japan Earthquake and Tsunami -- The Excess Demand for Used Cars The Excess Demand for Housing -- People As Sensors for Socio-Economic Recovery Activities -- Facebook Page Topics and the Excess Demand for Used Cars -- Data -- Topics on Twitter and the Excess Demand for Used Cars -- Public Sentiment and the Excess Demand for Used Cars -- Social Media Communication and the Excess Demand for Houses -- A Case Study of Hurricane Sandy -- The Excess Demand for Housing after Sandy -- Conclusion.
Contained By:	Springer eBooks
標題:	Online social networks. -
電子資源:	https://doi.org/10.1007/978-981-15-0825-7
ISBN:	9789811508257

Social media communication data for recovery = detecting socio-economic activities following a disaster /
Shibuya, Yuya.

Social media communication data for recoverydetecting socio-economic activities following a disaster /[electronic resource] :by Yuya Shibuya. - Singapore :Springer Singapore :2020. - xiii, 228 p. :ill., digital ;24 cm.

Declaration of Authorship -- Abstract -- Acknowledgements -- Introduction and Framework Introduction -- Concept of "People as Sensors" -- Methodology -- Empirical Studies of Socio-Economic Activities After the Great East Japan Earthquake and Tsunami -- The Excess Demand for Used Cars The Excess Demand for Housing -- People As Sensors for Socio-Economic Recovery Activities -- Facebook Page Topics and the Excess Demand for Used Cars -- Data -- Topics on Twitter and the Excess Demand for Used Cars -- Public Sentiment and the Excess Demand for Used Cars -- Social Media Communication and the Excess Demand for Houses -- A Case Study of Hurricane Sandy -- The Excess Demand for Housing after Sandy -- Conclusion.

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.

ISBN: 9789811508257

Standard No.: 10.1007/978-981-15-0825-7doiSubjects--Topical Terms:

624374
Online social networks.

LC Class. No.: HM742

Dewey Class. No.: 302.30285

Social media communication data for recovery = detecting socio-economic activities following a disaster /
LDR:03578nmm a2200325 a 4500 001 2214481
003 DE-He213
005 20200306120605.0
006 m d
007 cr nn 008maaau
008 201118s2020 si s 0 eng d
020 $a 9789811508257 $q (electronic bk.)
020 $a 9789811508240 $q (paper)
024 7 $a 10.1007/978-981-15-0825-7 $2 doi
035 $a 978-981-15-0825-7
040 $a GP $c GP
041 0 $a eng
050 4 $a HM742
072 7 $a KJQ $2 bicssc
072 7 $a BUS070030 $2 bisacsh
072 7 $a KJQ $2 thema
082 0 4 $a 302.30285 $2 23
090 $a HM742 $b .S555 2020
100 1 $a Shibuya, Yuya. $3 3445080
245 1 0 $a Social media communication data for recovery $h [electronic resource] : $b detecting socio-economic activities following a disaster / $c by Yuya Shibuya.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2020.
300 $a xiii, 228 p. : $b ill., digital ; $c 24 cm.
505 0 $a Declaration of Authorship -- Abstract -- Acknowledgements -- Introduction and Framework Introduction -- Concept of "People as Sensors" -- Methodology -- Empirical Studies of Socio-Economic Activities After the Great East Japan Earthquake and Tsunami -- The Excess Demand for Used Cars The Excess Demand for Housing -- People As Sensors for Socio-Economic Recovery Activities -- Facebook Page Topics and the Excess Demand for Used Cars -- Data -- Topics on Twitter and the Excess Demand for Used Cars -- Public Sentiment and the Excess Demand for Used Cars -- Social Media Communication and the Excess Demand for Houses -- A Case Study of Hurricane Sandy -- The Excess Demand for Housing after Sandy -- Conclusion.
520 $a 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.
650 0 $a Online social networks. $3 624374
650 0 $a Emergency management. $3 550721
650 1 4 $a Big Data/Analytics. $3 2186785
650 2 4 $a Business Information Systems. $3 892640
650 2 4 $a Econometrics. $3 542934
650 2 4 $a Big Data. $3 3134868
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-981-15-0825-7
950 $a Business and Management (Springer-41169)