Cross-Platform Bot Detection is a methodological framework in computational social science that integrates behavioral, temporal, and network-level features across multiple digital platforms to identify coordinated inauthentic behavior by distinguishing automated or manipulative accounts based on cross-platform activity patterns, thereby overcoming limitations of platform-specific detection approaches.
3
Publications
138
Citations
10
Authors
7
Institutions
Publications per year
2017–2026
3
Parents
Publications
3
1–4 of 3
Authors
10
- TL
1
h-index
- PZPengyuan Zhou
Hong Kong University of Science and Technology, Hong Kong SAR China
1 publications · 29 citations
1
h-index
- YL
1
h-index
- YLYangyang Li
China Academy of Information and Communications Technology, China
1 publications · 29 citations
1
h-index
- YY
1
h-index
1–5 of 10
Institutions
7
University of Leeds
Leeds, United Kingdom
1 h-index
1 publications
29 citations
California Southern University
Chandler, United States
1 h-index
1 publications
71 citations
Tsinghua University
Beijing, China
1 h-index
1 publications
29 citations
University of Science and Technology of China
Hefei, China
1 h-index
3 publications
87 citations
Beihang University
Beijing, China
1 h-index
1 publications
29 citations
Carnegie Mellon University
Pittsburgh, United States
1 h-index
2 publications
76 citations
University of Southern California
Los Angeles, United States
1 h-index
1 publications
71 citations
1–7 of 7
Venues
- First Monday
1 publications · 71 citations
1
h-index
- Proceedings of the International AAAI Conference on Web and Social Media
1 publications · 38 citations
1
h-index
- Social Network Analysis and Mining
1 publications · 12 citations
1–3