Multimodal Content Analysis

Multimodal Content Analysis is a computational methodology that integrates and interprets multiple forms of data—such as text, audio, visual, and sensory inputs—within a unified analytical framework to derive meaning, patterns, or insights from heterogeneous content sources.

179

Publications

9.8K

Citations

530

Authors

240

Institutions

Publications per year

2017–2026

96

Authors

530

  1. KL
    Kay L. O’Halloran

    Curtin University, Australia

    4 publications · 327 citations

    4

    h-index

  2. LC
    Laura Cervi

    Universitat Autònoma de Barcelona, Spain

    3 publications · 274 citations

    3

    h-index

  3. RR
    Rajiv Ratn Shah

    Indraprastha Institute of Information Technology Delhi, India

    3 publications · 112 citations

    3

    h-index

  4. ST
    Sabine Tan

    Curtin University, Australia

    3 publications · 248 citations

    3

    h-index

  5. TG
    Tanaya Guha

    University of Warwick, United Kingdom

    2 publications · 72 citations

    2

    h-index

1–5 of 530

Venues

  1. Journal of Pragmatics

    5 publications · 2K citations

    5

    h-index

  2. Discourse Context & Media

    4 publications · 256 citations

    4

    h-index

  3. Multimedia Tools and Applications

    4 publications · 215 citations

    4

    h-index

  4. 4

    h-index

  5. IEEE Transactions on Multimedia

    3 publications · 254 citations

    3

    h-index

1–5