Cited by 578Computational and Text Analysis MethodsFocus Groups and Qualitative MethodsSocial Media and Politics

The DOI matches its Crossref record; 47 of the 63 references it cites were found in a registry or an index.

Studying Reddit: A Systematic Overview of Disciplines, Approaches, Methods, and Ethics

Open access

Abstract

This article offers a systematic analysis of 727 manuscripts that used Reddit as a data source, published between 2010 and 2020. Our analysis reveals the increasing growth in use of Reddit as a data source, the range of disciplines this research is occurring in, how researchers are getting access to Reddit data, the characteristics of the datasets researchers are using, the subreddits and topics being studied, the kinds of analysis and methods researchers are engaging in, and the emerging ethical questions of research in this space. We discuss how researchers need to consider the impact of Reddit’s algorithms, affordances, and generalizability of the scientific knowledge produced using Reddit data, as well as the potential ethical dimensions of research that draws data from subreddits with potentially sensitive populations.

Overview

Integrity signals

Registry

Crossref · 10.1177/20563051211019004

Cites

47 of 47 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Research works printed but not linked: 11

  1. Baker M., 2016, Nature, 533, 353
  2. Baumgartner J., 2020, Proceedings of the International AAAI Conference on Web and Social Media, 14, 830
  3. Beninger K., 2017, The Sage handbook of social media research methods, 57
  4. Ferris L., 2011, International Journal of Occupational and Environmental Medicine, 2, 172
  5. Fiesler C., 2019, Proceedings of the ACM on Human-Computer Interaction, 3, 1
  6. Fiesler C., 2020, Proceedings of the International AAAI Conference on Web and Social Media, 14, 187
  7. Fiesler C., 2018, Proceedings of the International AAAI Conference on Web and Social Media, 12
  8. Isaak J., 2018, Computer, 51, 56
  9. Mittos A., 2020, Proceedings of the International AAAI Conference on Web and Social Media, 14, 452
  10. Reddit.com. (2020a). Reddit’s 2020 year in review. https://redditblog.com/2020/12/08/reddits-2020-year-in-review/
  11. Starbird K., 2014, iConference 2014 Proceedings, 654

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Metadata

Authors
Proferes, N., Jones, N., Gilbert, S., Fiesler, C., & Zimmer, M.
Affiliations
  • Arizona State University (US)
  • Office for National Statistics (GB)
  • University of Maryland, College Park (US)
  • University of Colorado Boulder (US)
  • Marquette University (US)
Corresponding author
Proferes, Nicholas
Venue
Social Media + Society
Published
2021-04
Volume
7
Issue
2
ISSN
2056-3051 (ISSN-L)
OpenAlex
W3167344319
Cited by
537
References
63
Citations by year
2026: 134 · 2025: 134 · 2024: 130 · 2023: 92 · 2022: 44 · 2021: 3
FWCI
170.55
Type
journal article
Language
en
Open access
Locations
  • Social Media + Society (publishedVersion, cc-by-nc)
  • e-Publications@Marquette (Marquette University) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Social Sciences › General Social Sciences › Computational and Text Analysis Methods
  • Social Sciences › Sociology and Political Science › Focus Groups and Qualitative Methods
  • Social Sciences › Communication › Social Media and Politics
Keywords
Reddit, online communities, subreddits, research ethics, data access, generalizability, sensitive populations, research methodology, disciplinary trends, social media research

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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