Multimodal Memes

Multimodal Memes is a computational framework that integrates multiple modes of semiotic resources—such as text, image, audio, and video—within a unified structure to model and analyze the production, dissemination, and interpretation of internet memes across diverse digital platforms.

111

Publications

5.1K

Citations

283

Authors

160

Institutions

Publications per year

2017–2026

97

Authors

283

  1. RK
    Roy Ka-Wei Lee

    Singapore University of Technology and Design, Singapore

    5 publications · 241 citations

    5

    h-index

  2. WC
    Wen-Haw Chong

    Singapore Management University, Singapore

    4 publications · 216 citations

    4

    h-index

  3. TC
    Tanmoy Chakraborty

    Indraprastha Institute of Information Technology Delhi, India

    3 publications · 207 citations

    3

    h-index

  4. PN
    Preslav Nakov

    Sofia University "St. Kliment Ohridski", Bulgaria

    3 publications · 207 citations

    3

    h-index

  5. MS
    Md Shad Akhtar

    Indraprastha Institute of Information Technology Delhi, India

    3 publications · 207 citations

    3

    h-index

1–5 of 283

Venues

  1. arXiv (Cornell University)

    Repository · 9 publications · 427 citations

    9

    h-index

  2. AoIR Selected Papers of Internet Research

    3 publications · 94 citations

    3

    h-index

  3. New Media & Society

    3 publications · 180 citations

    3

    h-index

  4. Social Media + Society

    2 publications · 271 citations

    2

    h-index

  5. Journal of Pragmatics

    2 publications · 120 citations

    2

    h-index

1–5