Emotion Annotation

Emotion Annotation is a systematic method within affective computing that involves the labeling of data with emotional attributes to enable the training and evaluation of models designed to recognize, interpret, or generate affective states.

556

Publications

36.7K

Citations

1.5K

Authors

525

Institutions

Publications per year

2017–2026

294

Authors

1.5K

  1. SM
    Saif M. Mohammad

    National Research Council Canada, Canada

    14 publications · 5.3K citations

    14

    h-index

  2. LD
    Laurence Devillers

    Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur, France

    11 publications · 551 citations

    11

    h-index

  3. CB
    Carlos Busso

    The University of Texas at Dallas, United States

    12 publications · 915 citations

    11

    h-index

  4. DD
    Dipankar Das

    Jadavpur University, India

    10 publications · 470 citations

    10

    h-index

  5. BW
    Björn W. Schuller

    Imperial College London, United Kingdom

    10 publications · 470 citations

    10

    h-index

1–5 of 1.5K

Venues

  1. IEEE Transactions on Affective Computing

    TAC · 27 publications · 3K citations

    20

    h-index

  2. arXiv (Cornell University)

    Repository · 28 publications · 1.6K citations

    18

    h-index

  3. IEEE Access

    9 publications · 320 citations

    8

    h-index

  4. Biomedical Informatics Insights

    7 publications · 431 citations

    7

    h-index

  5. Multimedia Tools and Applications

    6 publications · 164 citations

    6

    h-index

1–5