Cross-platform Detection

Cross-Platform Detection is a computational method designed to identify and verify misinformation by analyzing and correlating content across multiple digital platforms to detect consistent patterns of false or misleading information that transcend individual platform boundaries.

8

Publications

526

Citations

30

Authors

11

Institutions

Publications per year

2017–2026

6

Authors

30

  1. NM
    Nasir Memon

    New York University, United States

    1 publications · 16 citations

    1

    h-index

  2. MF
    Mattia Fazzini

    Georgia Institute of Technology, United States

    1 publications · 64 citations

    1

    h-index

  3. CG
    Christophe Gardella

    Sorbonne Université, France

    1 publications · 21 citations

    1

    h-index

  4. CS
    Christian Sticherling

    University Hospital of Basel, Switzerland

    1 publications · 21 citations

    1

    h-index

  5. SD
    Samuel D. Alcaine

    Cornell University, United States

    1 publications · 43 citations

    1

    h-index

1–5 of 30

Venues

  1. RNA

    1 publications · 114 citations

    1

    h-index

  2. Expert Systems with Applications

    1 publications · 175 citations

    1

    h-index

  3. The Analyst

    1 publications · 43 citations

    1

    h-index

  4. USENIX Security Symposium

    Conference · 1 publications · 22 citations

    1

    h-index

  5. First Monday

    1 publications · 71 citations

    1

    h-index

1–5