Cited by 93Spam and Phishing DetectionMisinformation and Its ImpactsHate Speech and Cyberbullying Detection

Changing Perspectives: Is It Sufficient to Detect Social Bots?

Grimme, Christian, Assenmacher, Dennis, Adam, Lena·2018·Lecture Notes in Computer Science

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Crossref · 10.1007/978-3-319-91521-0_32

Cites

17 of 17 references verified0 citation errors · 0 not checkable

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

  • Botometer's generality and ease of deployment are counterbalanced by reduced bot detection accuracy.

    “The generality and ease of deployment of this detector are however counterbalanced by a reduced bot detection accuracy [5, 17].”

    From A decade of social bot detection (2020) · cites this paper as [17]

  • Initial efforts towards adversarial bot detection were driven by the creativity of some researchers and only covered few cases with limited applicability.

    “The previous analysis highlights that initial efforts towards adversarial bot detection were driven by the creativity of some researchers and only covered few cases with limited applicability [9, 17].”

    From A decade of social bot detection (2020) · cites this paper as [17]

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Authors
Grimme, C., Assenmacher, D., & Adam, L.
Affiliations
University of Münster (DE)
Corresponding author
  • Grimme, Christian
  • Assenmacher, Dennis
Venue
Lecture Notes in Computer Science
Published
2018
Pages
445-461
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
OpenAlex
W2805358007
Cited by
93
References
17
Citations by year
2025: 9 · 2024: 15 · 2023: 11 · 2022: 11 · 2021: 10 · 2020: 31 · 2019: 6
FWCI
9.22
Type
conference paper
Language
en
Open access
closed
Locations
Lecture notes in computer science (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Spam and Phishing Detection
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
  • Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
Keywords
social bot detection, automated accounts, Twitter, hybrid detection, public opinion manipulation, strategic attack

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