Crowdsourced data in public administration research: A review and look to the future.

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Title: Crowdsourced data in public administration research: A review and look to the future.
Authors: Stritch, Justin M.1 (AUTHOR) jstritch@asu.edu, Pedersen, Mogens Jin2 (AUTHOR), Pezo, Ignacio1 (AUTHOR)
Source: Public Administration Review. Mar/Apr2025, Vol. 85 Issue 2, p581-593. 13p.
Subject Terms: *Research personnel, Public administration, Published articles, Data quality, Crowdsourcing
Abstract: Crowdsourcing platforms such as MTurk and Prolific have emerged as data sources for researchers in the social sciences. This article delves into the past, present, and future use of crowdsourced data in public administration scholarship. Through a review of published articles in top public administration journals (years 2013–2022), we uncover a general growth in the use of crowdsourced data over time. Additionally, we document how researchers have leveraged crowdsourced data to study a diverse range of themes and topics, with particular emphasis on survey experimental approaches and the examination of citizen attitudes and responses. Moreover, drawing on insights from a survey among quantitative public administration researchers, we discuss why the use of crowdsourced data is unlikely to diminish in the foreseeable future—despite ongoing debates regarding data quality and validity. We provide a set of guiding questions for researchers to consider when using crowdsourced data in public administration studies. [ABSTRACT FROM AUTHOR]
Copyright of Public Administration Review is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Crowdsourced data in public administration research: A review and look to the future.
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  Data: <searchLink fieldCode="JN" term="%22Public+Administration+Review%22">Public Administration Review</searchLink>. Mar/Apr2025, Vol. 85 Issue 2, p581-593. 13p.
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  Data: *<searchLink fieldCode="DE" term="%22Research+personnel%22">Research personnel</searchLink><br /><searchLink fieldCode="DE" term="%22Public+administration%22">Public administration</searchLink><br /><searchLink fieldCode="DE" term="%22Published+articles%22">Published articles</searchLink><br /><searchLink fieldCode="DE" term="%22Data+quality%22">Data quality</searchLink><br /><searchLink fieldCode="DE" term="%22Crowdsourcing%22">Crowdsourcing</searchLink>
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  Label: Abstract
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  Data: Crowdsourcing platforms such as MTurk and Prolific have emerged as data sources for researchers in the social sciences. This article delves into the past, present, and future use of crowdsourced data in public administration scholarship. Through a review of published articles in top public administration journals (years 2013–2022), we uncover a general growth in the use of crowdsourced data over time. Additionally, we document how researchers have leveraged crowdsourced data to study a diverse range of themes and topics, with particular emphasis on survey experimental approaches and the examination of citizen attitudes and responses. Moreover, drawing on insights from a survey among quantitative public administration researchers, we discuss why the use of crowdsourced data is unlikely to diminish in the foreseeable future—despite ongoing debates regarding data quality and validity. We provide a set of guiding questions for researchers to consider when using crowdsourced data in public administration studies. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Public Administration Review is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/puar.13823
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        Text: English
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        Type: general
      – SubjectFull: Public administration
        Type: general
      – SubjectFull: Published articles
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      – SubjectFull: Data quality
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      – SubjectFull: Crowdsourcing
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              Text: Mar/Apr2025
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              Y: 2025
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