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Cited by 66Ethics and Social Impacts of AIFocus Groups and Qualitative MethodsData Analysis and Archiving

The Ethical Challenges of Publishing Twitter Data for Research Dissemination

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Webb, Helena, Jirotka, Marina, Stahl, Bernd Carsten, Housley, William, Edwards, Adam, Williams, Matthew, Procter, Rob, Rana, Omer +1 more·2017·Proceedings of the 2017 ACM on Web Science Conference
DOI 10.1145/3091478.3091489
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Abstract

Empirical research involving the analysis of Internet-based data raises a number of ethical challenges. One instance of this is the analysis of Twitter data, in particular when specific tweets are reproduced for the purposes of dissemination. Although Twitter is an open platform it is possible to question whether this provides a sufficient ethical justification to collect, analyse and reproduce tweets for the purposes of research or whether it is necessary to also undertake specific informed consent procedures. This paper reports on an ethics consultation that formed part of a wider research study and that aimed to identify best practice procedures for the publication of Twitter data in research findings. We focus largely on the UK context and draw on the outcomes of the consultation to highlight the range and depth of ethical issues that arise in this area. We can see Twitter as a case study for a wide number of data sources used in Web Science. This is a highly complex landscape in which questions crystallise around fundamental principles such as informed consent, anonymisation and the minimisation of harm. Furthermore, tensions exist between commercial, regulatory and academic practices, and there are also circumstances in which good ethical practice might compromise academic integrity. There is an absence of consensus in Web science and related fields over how to resolve these issues and we argue that constructive debate is necessary in order to take a proactive approach towards good practice.

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  • Making social media data identifiable in ways not originally intended by the user who posted the content could place an individual at risk of harm or divulge sensitive health information.

    “Precautions are needed to ensure that data is not made identifiable in ways that were not originally intended by the user who posted the content, as this could place an individual at risk of harm or divulge sensitive health information (Webb et al., 2017; Williams, Burnap, & Sloan, 2017).”

    From Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice (2020) · cites this paper as Webb et al., 2017

    Section 4.3, p. 6, says users may not expect their tweets to be republished for other audiences and that revealing their identities could put them at risk of harm. Section 4.4, p. 7, explains how published tweet text can reveal a user's identity through search. The passages do not support the specific claim about divulging sensitive health information. (LLM, conf=0.87)

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  1. [1][1] For overview see: Gayo-Avello, D. 2013. A meta-analysis of state of the art electoral prediction from Twitter data. Social Science Computer Review 31, 6 (Aug. 2013) 649-679. DOI=10.1177/0894439313493979 - · DOI
  2. [4][4] For overview see: Marwick, A. 2013 Ethnographic and Qualitative Research on Twitter. In Weller, K., Bruns, A., Puschmann, C., Burgess, J. and Mahrt, M. (eds.) Twitter and Society New York: Peter Lang, 109-122. -
  3. [5][5] For example, see: Stahl, B. C. Heersmink, R. Goujon, P. Flick, C. van den Hoven, J. Wakunuma, K. Veikko Ikonen, V.T.T. and Rader, M. 2010. Identifying the ethics of Emerging Information and Communication Technologies. International Journal of Technoethics 1,4,20-38; boyd, d and Crawford, K. 2012 Critical questions for big data Information, Communication and Society 15,6. 662-679 DOI= 10.1080/1369118X.2012.678878; Zimmer, M. 2010. 'But the data is already public' on the ethics of research in Facebook. Ethics and Information Technology 12,4, 313-325; Zwitter, A.J. 2014. Big Data Ethics Big Data and Society 1,2 Nov 2014 doi/10.1177/2053951714559253; Schroeder, R. 2014. Big Data and the brave new world of social media research Big Data and Society 1,2 Dec 2014. DOI=10.1177/2053951714563194. - · DOI · Paper page
  4. [6][6] For example see: Neuhas, F. and Webmoor, 2012. Agile ethics for massified research and visualization. Information, Communication and Society 15,1, 43-65 DOI= 10.1080/1369118X.2011.616519. And: McNeily, M Hutton, L. and Henderson, T. 2013. Understanding ethical concerns in social media privacy studies. In Proceedings of the ACM CSCW Workshop on measuring networked social privacy: Qualitative and Quantitative approaches. - · DOI
  5. [7][7] For overview see: Zimmer, M. and Proferes, N.J. 2014. A topology of Twitter research: disciplines, methods and ethics. Aslib Journal of - Information Management 66,3, 250-261. , 1-10. DOI= 10.1108/AJIM09-2013-0083. - · DOI
  6. [9][9] Webb, H., Jirotka, M., Carsten Stahl, B., Housley, W., Edwards, A., Williams, M., Procter, R., Rana, O. and Burnap, P. (2015). Digital wildfires: hyper-connectivity, havoc and a global ethos to govern social media. Computers and Society 45(3), 193-201. DOI=10.1145/2874239.2874267 - · DOI
  7. [10][10] For further details of these approaches see: Housley, W., Webb, H., Williams, M. et. al. (forthcoming) Social Media, Interaction and Categorisation: The Case of Twitter Campaigns. Social Media and Society special issue on Social Movements and Social Media. And: Tolmie, P., Procter, R., Rouncefield, M., Liakata, M. and Zubiaga, A. Microblog Analysis as a programme of work. Submitted to ACM Transactions on Social Computing. -
  8. [16][16] Moffat, A. and Koene, A. 2016. Public Outreach Evaluation Tool (TOOL). Poster presented at the Social Media and Society Conference July 2016. -
  9. [19][19] Markham, A. 2005. 'Go ugly early': Fragmented narrative and bricolage as interpretive method. Qualitative Inquiry 11,16, 813-819 DOI=10.1177/1077800405280662. - · DOI
  10. [21][21] See for example: Moran, S., Luger, E. and Rodden, T. 2014. An emerging toolkit for attaining informed consent in UbiComp. UbiComp '14 Adjunct Sep 2014 Available online at: http://ubicomp.org/ubicomp2014/proceedings/ubicomp\_adjunct/wo rkshops/Consent/p635-moran.pdf

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Authors
Webb, H., Jirotka, M., Stahl, B. C., Housley, W., Edwards, A., Williams, M., Procter, R., Rana, O., & Burnap, P.
Affiliations
  • University of Oxford (GB)
  • De Montfort University (GB)
  • Cardiff University (GB)
  • University of Warwick (GB)
ORCID
Venue
Proceedings of the 2017 ACM on Web Science Conference
Publisher
ACM
Published
2017-06-25
Pages
339-348
DOI
10.1145/3091478.3091489
OpenAlex
W2730767630
Cited by
66
References
1
Citations by year
2026: 4 · 2025: 3 · 2024: 4 · 2023: 5 · 2022: 7 · 2021: 11 · 2020: 13 · 2019: 11 · 2018: 7 · 2017: 1
FWCI
21.82
Type
conference paper
Language
en
Open access
Licence
Locations
  • ACM Web Science Conference (WebSci) (publishedVersion, cc-by)
  • Warwick Research Archive Portal (University of Warwick) (acceptedVersion)
  • ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
  • Warwick Research Archive Portal (University of Warwick) (submittedVersion)
Funders
Economic and Social Research Council (ES/L0133981)
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Social Sciences › Sociology and Political Science › Focus Groups and Qualitative Methods
  • Social Sciences › Sociology and Political Science › Data Analysis and Archiving
Keywords
tweets, research ethics, informed consent, data anonymization, research dissemination, open data portals, web science, academic integrity, ethics consultation, best practice guidelines

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