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Probing construct validity in data-driven disaster analysis

Chung, WT and Lin, YR (2017) Probing construct validity in data-driven disaster analysis. In: UNSPECIFIED.

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Abstract

© 2016 IEEE. In this position paper, we discuss the promise and peril in data-driven disaster analysis. We argue for the importance of being sensitive to the construct validity issue prevailed in many big data studies and propose a research strategy as a remedy for such issue. Our strategy comprises three steps: theory-driven set-up first, statistic assessment follows, and qualitative inquiry for further calibration. The goal is to translate activity signals captured from data to proper social or behavioral interpretation. We exemplify the use of the proposed research strategy through a study of risk perception following a disaster event, and discuss the strategy's potential and limitation.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Chung, WT
Lin, YRyurulin@pitt.eduYURULIN
Contributors:
ContributionContributors NameEmailPitt UsernameORCID
CorrespondentLin, Yu-Ruyurulin@pitt.eduYURULINUNSPECIFIED
Date: 6 January 2017
Date Type: Publication
Journal or Publication Title: Proceedings - 2016 IEEE 2nd International Conference on Collaboration and Internet Computing, IEEE CIC 2016
Page Range: 500 - 501
Event Type: Conference
DOI or Unique Handle: 10.1109/cic.2016.076
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISBN: 9781509046072
Date Deposited: 30 Jun 2017 14:56
Last Modified: 18 Oct 2017 06:55
URI: http://d-scholarship.pitt.edu/id/eprint/32601

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