The PERVADE team has tackled a wide range of topics and stakeholders as it relates to pervasive data ethics. In addition to the subcategories below, see our manifesto on trustworthy pervasive data research for a high-level overview of our work.
Fiesler, Zimmer, and Vitak received NSF funding from the Ethical & Responsible Research (ER2) directorate in 2024.
Multiple papers are currently under review based on this work.
Michael Zimmer, Casey Fiesler, and Jessica Vitak. 2026. The PERVADE Data Ethics Tool: Supporting Reflexive Research Ethics Education. In Proceedings of the 57th ACM Technical Symposium on Computer Science Education V.2), ACM. https://doi.org/10.1145/3770761.3777113
This paper summarizes our demonstration on educational uses for the PERVADE decision support tool.
The research team has a long history of studying the attitudes and behaviors within user communities — the people whose content is being scraped and analyzed more and more often.
Fiesler, C., & Proferes, N. (2018). “Participant” perceptions of Twitter research ethics. Social Media+ Society, 4(1), 2056305118763366.
The majority of Twitter users in this survey were unaware that their tweets might be used by researchers, and felt that such research should not happen without consent. However, attitudes are also highly contextual, depending on factors such as what the research is about and how it is conducted.
Gilbert, S., Vitak, J., & Shilton, K. (2021). Measuring Americans’ comfort with research uses of their social media data. Social Media+ Society, 7(3), 20563051211033824.
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Gilbert, S., Shilton, K., & Vitak, J. (2023). When research is the context: Cross-platform user expectations for social media data reuse. Big Data & Society, 10(1), 20539517231164108.
This set of factorial vignette studies revealed that end-user evaluation of the acceptability of research varies based on contexts such as type platform, type of content, awareness of data collection, and purpose of the research. Consent and awareness were the most important factors for comfort with research.
Dym, B., & Fiesler, C. (2020). Ethical and Privacy Considerations for Research Using Online Fandom Data. Transformative Works and Cultures, 33.
This study examined transformative fandom (including both social media spaces and content such as fanfiction) as a site for research, and due to the demographics of this community and the study sample, also reveals insights related to privacy-vulnerable populations such as queer people. Based on concerns surfaced, best practices are recommended around preserving privacy, respecting community norms, and avoiding extractive practices.
Klassen, S., & Fiesler, C. (2022). “This isn’t your data, friend”: Black Twitter as a case study on research ethics for public data. Social Media+ Society, 8(4), 20563051221144317.
This study examined Black Twitter as a site for research, asking community members how they felt about researchers using their content. Comfort levels depended on factors such as the type of research and positionality of the researchers. Participants recommended best practices for researchers such as cultivating cultural competency and conducting research transparently.
Zimmer, M., & Logan, S. (2022). Privacy concerns with using public data for suicide risk prediction algorithms: a public opinion survey of contextual appropriateness. Journal of Information, Communication and Ethics in Society, 20(2), 257-272.
This study examined people’s perceptions of the use of publicly available socioeconomic data (e.g., financial, legal, life events) for use in suicide prediction algorithms. Participants were especially concerned about the risks associated with sensitive data such as arrest records and income.
In this thread of research, we explore the attitudes, practices, and needs of those conducting research with pervasive data. Read more about what researchers feel confident about, and what they need more guidance on.
Vitak, J., Shilton, K., & Ashktorab, Z. (2016). Beyond the Belmont principles: Ethical challenges, practices, and beliefs in the online data research community. In Proceedings of the 19th ACM conference on computer-supported cooperative work & social computing (pp. 941-953).
A survey of internet researchers found that there was limited consensus on the relevant ethical issues in social computing research (including research with public social media content), and associated best practices.
Fiesler, C., Zimmer, M., Proferes, N., Gilbert, S., & Jones, N. (2024). Remember the Human: A Systematic Review of Ethical Considerations in Reddit Research. Proceedings of the ACM on Human-Computer Interaction, 8(GROUP), 1-33.
This systematic literature review of ethical considerations described in published papers that use Reddit data reveals common ethical issues and ethically motivated methodological decisions among researchers, concluding with a set of recommended best practices.
Ajmani, L. H., Chancellor, S., Mehta, B., Fiesler, C., Zimmer, M., & De Choudhury, M. (2023, June). A systematic review of ethics disclosures in predictive mental health research. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (pp. 1311-1323).
This systematic literature review of ethical disclosures in predictive mental health research revealed prioritization of data-driven over human-centered disclosures and inconsistently reported ethical considerations.
Historically, the bulk of research ethics practices and regulations have been mediated through university-based IRBs. However, much pervasive computing research falls outside of formal university-based ethics infrastructures. See our publications assessing and comparing how ethics regulators respond to this dis-junction.
Vitak, J., Proferes, N., Shilton, K., & Ashktorab, Z. (2017). Ethics regulation in social computing research: Examining the role of institutional review boards. Journal of Empirical Research on Human Research Ethics, 12(5), 372-382.
This survey of U.S. IRB staff pointed to a lack of consensus regarding the applicability of IRB review to some types of social computing research, including research with public data, but a willingness to work closely with researchers in making ethical decisions.
Pater, J., Fiesler, C., & Zimmer, M. (2022). No humans here: Ethical speculation on public data, unintended consequences, and the limits of institutional review. Proceedings of the ACM on Human-Computer Interaction, 6(GROUP), 1-13.
This design fiction presents a fictional case study of a research ethics dilemma that falls through regulatory gaps and results in unintended negative consequences.
Fiesler, C., Beard, N., & Keegan, B. C. (2020, May). No robots, spiders, or scrapers: Legal and ethical regulation of data collection methods in social media terms of service. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 14, pp. 187-196).
This analysis of data scraping provisions in social media terms of service, and finds that they typically lack relevant context for ethical decision-making, concluding that such decisions should extend beyond TOS and consider contextual factors of the data source and research.
Brown, M. A., Gruen, A., Maldoff, G., Messing, S., Sanderson, Z., & Zimmer, M. (2025). Web scraping for research: Legal, ethical, institutional, and scientific considerations. Big Data & Society, 12(4), 20539517251381686.
This paper presents an overview of the U.S. regulatory environment impacting when and how researchers can access, collect, store, and share data via scraping.