CoChat
Sign Up
Cited by 39Misinformation and Its ImpactsJournalism and Media StudiesComplex Network Analysis Techniques

Journalists on Twitter: self-branding, audiences, and involvement of bots

Varol, Onur, Uluturk, Ismail·2020·Journal of Computational Social Science
DOI 10.1007/s42001-019-00056-6
Open this paper in CoChat — free account

Integrity signals

Registry

Crossref · 10.1007/s42001-019-00056-6

Cites

53 of 53 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?

  • Fake followers used to increase online popularity and manipulate the online perception of journalist accounts have similar patterns.

    “A subsequent study on journalists on Twitter identified similar patterns in fake followers which were used to increase online popularity and manipulate the online perception of journalist accounts [48].”

    From Unsupervised detection of coordinated fake-follower campaigns on social media (2024) · cites this paper as [48]

  • Accounts created on similar dates and following users successively are more likely to be automated.

    “While coordination in account activity does not necessarily coincide with automation [36,37], accounts created on similar dates and following users successively are more likely to be automated [3,48].”

    From Unsupervised detection of coordinated fake-follower campaigns on social media (2024) · cites this paper as [48]

  • Bots are maliciously used on social media platforms to spread disinformation and manipulate user popularity and engagement metrics.

    “However, bots are also maliciously used on social media platforms to spread disinformation and manipulate user popularity and engagement metrics [6,39,48].”

    From Unsupervised detection of coordinated fake-follower campaigns on social media (2024) · cites this paper as [48]

  • Analysis of followers of 1318 Twitter accounts supports earlier findings regarding existence of coordinated accounts that exhibit anomalous following patterns on Twitter.

    “Our analysis of the followers of 1318 Twitter accounts supports the earlier findings regarding the existence of coordinated accounts that exhibit anomalous following patterns on Twitter [9,48].”

    From Unsupervised detection of coordinated fake-follower campaigns on social media (2024) · cites this paper as [48]

  • Botometer currently does not use the 'verified' status as a feature because it could lead to false negatives.

    “Botometer currently does not use the 'verified' status as a feature because it could lead to false negatives [45].”

    From Detection of Novel Social Bots by Ensembles of Specialized Classifiers (2020) · cites this paper as [45]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Varol, O., & Uluturk, I.
Affiliations
  • Northeastern University (US)
  • University of South Florida (US)
Corresponding author
Varol, Onur
ORCID
Venue
Journal of Computational Social Science
Publisher
Springer Science and Business Media LLC
Published
2019-09-25
Volume
3
Issue
1
Pages
83-101
ISSN
  • 2432-2717 (ISSN-L)
  • 2432-2725
DOI
10.1007/s42001-019-00056-6
OpenAlex
W2975786027
Cited by
39
References
53
Citations by year
2025: 4 · 2024: 8 · 2023: 6 · 2022: 4 · 2021: 2 · 2020: 15
FWCI
9.90
Type
journal article
Language
en
Open access
closed
Licence
Locations
  • Journal of Computational Social Science (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
  • Social Sciences › Communication › Journalism and Media Studies
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
Keywords
journalists, Twitter, social bots, bot detection, follower networks, audience composition, personal branding, misinformation, information operations, account verification, online popularity, editorial oversight

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