Understanding Barriers to Novel Data Linkages: Topic Modeling of the Results of the LifeInfo Survey

Clarke, H, Clark, S orcid.org/0000-0003-4090-6002, Birkin, M et al. (3 more authors) (2021) Understanding Barriers to Novel Data Linkages: Topic Modeling of the Results of the LifeInfo Survey. Journal of Medical Internet Research, 23 (5). e24236. ISSN 1438-8871

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2021, Holly Clarke, Stephen Clark, Mark Birkin, Heather Iles-Smith, Adam Glaser, Michelle A Morris. Originally published in the Journal of Medical Internet Research. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
Keywords: topic modeling; text analysis; lifestyle data; consumer data; mHealth; loyalty card; fitness tracker; data linkage; data sharing; public attitudes; public opinion
Dates:
  • Accepted: 12 April 2021
  • Published (online): 17 May 2021
  • Published: 17 May 2021
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds)
Funding Information:
FunderGrant number
ESRC (Economic and Social Research Council)ES/S007164/1
Depositing User: Symplectic Publications
Date Deposited: 27 Apr 2021 08:56
Last Modified: 19 Aug 2021 13:24
Status: Published
Publisher: JMIR Publications
Identification Number: https://doi.org/10.2196/24236

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