Don’t quote me: reverse identification of research participants in social media studies

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dc.contributor.authorAyers, John W.
dc.contributor.authorCaputi, Theodore L.
dc.contributor.authorNebeker, Camille
dc.contributor.authorDredze, Mark
dc.contributor.funderUS-Ireland Alliance
dc.contributor.funderRobert Wood Johnson Foundation
dc.contributor.funderNational Institute of Mental Health
dc.contributor.funderBurroughs Wellcome Fund
dc.date.accessioned2018-09-27T12:08:23Z
dc.date.available2018-09-27T12:08:23Z
dc.date.issued2018
dc.description.abstractWe investigated if participants in social media surveillance studies could be reverse identified by reviewing all articles published on PubMed in 2015 or 2016 with the words “Twitter” and either “read,” “coded,” or “content” in the title or abstract. Seventy-two percent (95% CI: 63–80) of articles quoted at least one participant’s tweet and searching for the quoted content led to the participant 84% (95% CI: 74–91) of the time. Twenty-one percent (95% CI: 13–29) of articles disclosed a participant’s Twitter username thereby making the participant immediately identifiable. Only one article reported obtaining consent to disclose identifying information and institutional review board (IRB) involvement was mentioned in only 40% (95% CI: 31–50) of articles, of which 17% (95% CI: 10–25) received IRB-approval and 23% (95% CI:16–32) were deemed exempt. Biomedical publications are routinely including identifiable information by quoting tweets or revealing usernames which, in turn, violates ICMJE ethical standards governing scientific ethics, even though said content is scientifically unnecessary. We propose that authors convey aggregate findings without revealing participants’ identities, editors refuse to publish reports that reveal a participant’s identity, and IRBs attend to these privacy issues when reviewing studies involving social media data. These strategies together will ensure participants are protected going forward.en
dc.description.sponsorshipNational Institute of Mental Health (R21MH103603); Robert Wood Johnson Foundation (#72876, 2015-2017); US-Ireland Alliance (George J. Mitchell Scholarship Fund).en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.articleid30
dc.identifier.citationAyers, J. W., Caputi, T. L., Nebeker, C. and Dredze, M. (2018) 'Don’t quote me: reverse identification of research participants in social media studies', npj Digital Medicine, 1(1), 30 (2pp). doi: 10.1038/s41746-018-0036-2en
dc.identifier.doi10.1038/s41746-018-0036-2
dc.identifier.endpage2
dc.identifier.issn2398-6352
dc.identifier.journaltitleNPJ Dogital Medicineen
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/10468/6944
dc.identifier.volume1
dc.language.isoenen
dc.publisherSpringer Natureen
dc.relation.urihttps://www.nature.com/articles/s41746-018-0036-2
dc.rights© 2018, the Authors. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectEpidemiologyen
dc.subjectTranslational researchen
dc.subjectSocial media surveillanceen
dc.subjectReverse identificationen
dc.subjectAnonymisationen
dc.titleDon’t quote me: reverse identification of research participants in social media studiesen
dc.typeArticle (peer-reviewed)en
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