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Saving social media data: Understanding data management practices among social media researchers and their implications for archives

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  • Libby Hemphill
  • Margaret L. Hedstrom
  • Susan Hautaniemi Leonard

Abstract

Social media data (SMD) offer researchers new opportunities to leverage those data for their work in broad areas such as public opinion, digital culture, labor trends, and public health. The success of efforts to save SMD for reuse by researchers will depend on aligning data management and archiving practices with evolving norms around the capture, use, sharing, and security of datasets. This paper presents an initial foray into understanding how established practices for managing and preserving data should adapt to demands from researchers who use and reuse SMD, and from people who are subjects in SMD. We examine the data management practices of researchers who use SMD through a survey, and we analyze published articles that used data from Twitter. We discuss how researchers describe their data management practices and how these practices may differ from the management of conventional data types. We explore conceptual, technical, and ethical challenges for data archives based on the similarities and differences between SMD and other types of research data, focusing on the social sciences. Finally, we suggest areas where archives may need to revise policies, practices, and services in order to create secure, persistent, and usable collections of SMD.

Suggested Citation

  • Libby Hemphill & Margaret L. Hedstrom & Susan Hautaniemi Leonard, 2021. "Saving social media data: Understanding data management practices among social media researchers and their implications for archives," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(1), pages 97-109, January.
    • Handle: RePEc:bla:jinfst:v:72:y:2021:i:1:p:97-109
    DOI: 10.1002/asi.24368
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    References listed on IDEAS

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    1. Matthew S. Mayernik, 2016. "Research data and metadata curation as institutional issues," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(4), pages 973-993, April.
    2. Arkaitz Zubiaga, 2018. "A longitudinal assessment of the persistence of twitter datasets," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(8), pages 974-984, August.
    3. Ixchel M. Faniel & Adam Kriesberg & Elizabeth Yakel, 2016. "Social scientists' satisfaction with data reuse," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(6), pages 1404-1416, June.
    4. Stefanie Haustein & Timothy D. Bowman & Kim Holmberg & Andrew Tsou & Cassidy R. Sugimoto & Vincent Larivière, 2016. "Tweets as impact indicators: Examining the implications of automated “bot” accounts on Twitter," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(1), pages 232-238, January.
    5. Sara Randall & Ernestina Coast, 2016. "The quality of demographic data on older Africans," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 34(5), pages 143-174.
    6. Youngseek Kim & Jeffrey M. Stanton, 2016. "Institutional and individual factors affecting scientists' data-sharing behaviors: A multilevel analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(4), pages 776-799, April.
    7. Carol Tenopir & Elizabeth D Dalton & Suzie Allard & Mike Frame & Ivanka Pjesivac & Ben Birch & Danielle Pollock & Kristina Dorsett, 2015. "Changes in Data Sharing and Data Reuse Practices and Perceptions among Scientists Worldwide," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-24, August.
    8. Lisa M Federer & Ya-Ling Lu & Douglas J Joubert & Judith Welsh & Barbara Brandys, 2015. "Biomedical Data Sharing and Reuse: Attitudes and Practices of Clinical and Scientific Research Staff," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-17, June.
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