Who decides what is read on Goodreads? Uncovering sponsorship and its implications for scholarly research.

Attracted by the promise of a broader and more egalitarian sample of readers than published book reviews provide, researchers are increasingly scraping social reviewing platforms like Goodreads for data about readers' behavior. Yet, treating online book reviews as direct proxies for readers and book...

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Publicado en:Big Data & Society Vol. 12; no. 3; pp. 1 - 18
Autores principales: Hu, Yuerong, Diesner, Jana, Underwood, Ted, LeBlanc, Zoe, Layne-Worthey, Glen, Downie, John Stephen
Formato: Artículo
Publicado: Sage Publications Inc. Jul-Sep2025
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jul-Sep2025
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        atl: Who decides what is read on Goodreads? Uncovering sponsorship and its implications for scholarly research.
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          Hu, Yuerong
          Diesner, Jana
          Underwood, Ted
          LeBlanc, Zoe
          Layne-Worthey, Glen
          Downie, John Stephen
        affil:
          Department for Information and Library Science, Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, USA
          School of Social Sciences and Technology, Technical University Munich, Munich, Germany
          School of Information Sciences, University of Illinois Urbana Champaign, Champaign, IL, USA
          Department of English, University of Illinois Urbana Champaign, Champaign, IL, USA
      su:
        Social media
        Scholarly method
        Digital technology
        Patronage
        Internet publishing
        Data analysis
      sug:
        subj:
          Social media
          Scholarly method
          Digital technology
          Patronage
          Internet publishing
          Data analysis
      keyword:
        Critical data studies
        digital humanities
        incentivized reviews
        online book reviews
        platform capitalism
        sociotechnical data practices
      ab: Attracted by the promise of a broader and more egalitarian sample of readers than published book reviews provide, researchers are increasingly scraping social reviewing platforms like Goodreads for data about readers' behavior. Yet, treating online book reviews as direct proxies for readers and books can be problematic, as they are socially and technically constructed artifacts shaped by platform dynamics, whether between developers and users, or book industry stakeholders and reviewers. To uncover these complexities, we computationally curated 331,211 self-identified incentivized book reviews to understand the growth of incentivized content, and how these purportedly equal-access social reviewing spaces are re-inscribing the inequalities of traditional book reviewing and publishing. Our findings underscore the necessity of critical examination of both online book reviewing and cultural datasets derived from social media platforms. With the growing restrictions on access to platform data for research, this study also demonstrates the potential for a mixed-method analysis of historical scraped datasets; an approach that will likely be of interest to many researchers working with cultural data moderated by black-box algorithms. With this method, our research reveals for the first time the scale of the phenomena of incentivized book reviews that is well known to users of Goodreads but remains largely anecdotal. Additionally, it illuminates the rise of sponsored content while contributing to broader discussions on computational approaches to digital economies of prestige and the responsible use of platform-mediated cultural datasets across disciplines.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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          year: 2025
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