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Estimating suicide occurrence statistics using Google Trends

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Kristoufek, Ladislav, Moat, Helen Susannah and Preis, Tobias (2016) Estimating suicide occurrence statistics using Google Trends. EPJ Data Science, 5 (1). 32. doi:10.1140/epjds/s13688-016-0094-0 ISSN 2193-1127.

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Official URL: http://dx.doi.org/10.1140/epjds/s13688-016-0094-0

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Abstract

Data on the number of people who have committed suicide tends to be reported with a substantial time lag of around two years. We examine whether online activity measured by Google searches can help us improve estimates of the number of suicide occurrences in England before official figures are released. Specifically, we analyse how data on the number of Google searches for the terms ‘depression’ and ‘suicide’ relate to the number of suicides between 2004 and 2013. We find that estimates drawing on Google data are significantly better than estimates using previous suicide data alone. We show that a greater number of searches for the term ‘depression’ is related to fewer suicides, whereas a greater number of searches for the term ‘suicide’ is related to more suicides. Data on suicide related search behaviour can be used to improve current estimates of the number of suicide occurrences.

Item Type: Journal Article
Subjects: H Social Sciences > HV Social pathology. Social and public welfare
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources
Divisions: Faculty of Social Sciences > Warwick Business School
Library of Congress Subject Headings (LCSH): Suicide -- Statistics -- England, Depression, Mental -- Statistics -- England, Internet searching, Google (Firm)
Journal or Publication Title: EPJ Data Science
Publisher: Springer
ISSN: 2193-1127
Official Date: 8 November 2016
Dates:
DateEvent
8 November 2016Published
29 October 2016Accepted
Volume: 5
Number: 1
Article Number: 32
DOI: 10.1140/epjds/s13688-016-0094-0
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons)
Date of first compliant deposit: 31 March 2017
Date of first compliant Open Access: 4 April 2017
Funder: Research Councils UK (RCUK), Grantová agentura České republiky [Czech Science Foundation] (AVČR)
Grant number: EP/K039830/1 (RCUK), 16-00027S (AVČR)

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