Cited by 423Misinformation and Its ImpactsComplex Network Analysis TechniquesPublic Relations and Crisis Communication

Rumors, False Flags, and Digital Vigilantes: Misinformation on Twitter after the 2013 Boston Marathon Bombing

Open access
Kate Starbird, Jim Maddock, Mania Orand, Peg Achterman, Robert M. Mason·2014·iConference 2014 Proceedings

Abstract

The Boston Marathon bombing story unfolded on every possible carrier of information available in the spring of 2013, including Twitter. As information spread, it was filled with rumors (unsubstantiated information), and many of these rumors contained misinformation. Earlier studies have suggested that crowdsourced information flows can correct misinformation, and our research investigates this proposition. This exploratory research examines three rumors, later demonstrated to be false, that circulated on Twitter in the aftermath of the bombings. Our findings suggest that corrections to the misinformation emerge but are muted compared with the propagation of the misinformation. The similarities and differences we observe in the patterns of the misinformation and corrections contained within the stream over the days that followed the attacks suggest directions for possible research strategies to automatically detect misinformation.

Integrity signals

Registry

Crossref · 10.9776/14308

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

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

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?

  • Starbird et al. (2014) found that Twitter users poorly distinguished truth from hoaxes in the 2013 Boston Marathon bombings, with ratios of 44:1, 18:1, and 5:1 favouring tweets supporting false rumours.

    “In contrast, in their study of the 2013 Boston Marathon bombings, Starbird et al. (2014) found that Twitter users did not do so well in distinguishing between the truth and hoaxes.Examining three different rumours, they found the equivalent ratio to be 44:1, 18:1, and 5:1 in favour of tweets supporting false rumours.”

    From Detection and Resolution of Rumours in Social Media (2019) · cites this paper as Starbird et al. 2014

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Starbird, K., Maddock, J., Orand, M., Achterman, P., & Mason, R. M.
Affiliations
University of Washington (US)
Venue
iConference 2014 Proceedings
Publisher
iSchools
Published
2014-03-01
OpenAlex
W31250479
Cited by
423
References
2
Citations by year
2026: 5 · 2025: 12 · 2024: 19 · 2023: 24 · 2022: 28 · 2021: 63 · 2020: 76 · 2019: 44 · 2018: 52 · 2017: 42 · 2016: 21 · 2015: 23 · 2014: 13
FWCI
106.25
Type
conference paper
Language
en
Open access
Locations
  • iConference (publishedVersion)
  • Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) (submittedVersion)
Funders
National Science Foundation (1243170, 1342252)
Topics
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
  • Social Sciences › Communication › Public Relations and Crisis Communication
Keywords
Boston Marathon bombing, misinformation, rumors, Twitter, crowdsourced data, misinformation detection

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.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review