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Topic · Experimental and Cognitive Psychology

Emotion and Mood Recognition

Emotion and Mood Recognition is a research topic within Experimental and Cognitive Psychology. Science Explorer counts 19k research works in it since 1953. 9.8% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the recognition and analysis of emotions from various modalities such as facial expressions, physiological signals, and speech. It explores the use of deep learning, affective computing, and multimodal data for emotion recognition in applications including human-computer interaction.

  • Emotion Recognition
  • Multimodal Data
  • Facial Expression
  • Physiological Signals
  • Deep Learning
  • Affective Computing
  • Speech Emotion
  • Feature Extraction
  • Database
  • Human-Computer Interaction
Research works
19k
fractional, since 1953
In the world top 10%
1.9k
per year above
Top-10% rate
9.8%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+132%
the tick is no change
Largest producer
China
37% of the 10 largest, 2022-now
Emotion and Mood Recognition

Which countries lead Emotion and Mood Recognition research?

By volume, China and India publish the most (3k and 2.5k works in 2022-now).

By volume, 2022-now

  1. 1 China 3k works
  2. 2 India 2.5k works
  3. 3 United States 907 works
  4. 4 Japan 368 works
  5. 5 United Kingdom 265 works
  6. 6 South Korea 258 works
  7. 7 Indonesia 218 works
  8. 8 Germany 218 works
  9. 9 Italy 193 works
  10. 10 Canada 161 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 37.4%India: 30.5%United States: 11.3%Japan: 4.6%6 others listed: 16.3%37%largest
China3,009 · 37.4%India2,453 · 30.5%United States907 · 11.3%Japan368 · 4.6%6 others listed1,312 · 16.3%

Shares of the rows listed above, not of the whole node.

Which institutions lead Emotion and Mood Recognition research?

By volume in 2022-now, SRM Institute of Science and Technology publishes the most Emotion and Mood Recognition research, followed by Chinese Academy of Sciences and Amrita Vishwa Vidyapeetham.

By volume, 2022-now

  1. 1 SRM Institute of Science and TechnologyIndia 102 works
  2. 2 Chinese Academy of SciencesChina 93 works
  3. 3 Amrita Vishwa VidyapeethamIndia 66 works
  4. 4 Vellore Institute of Technology UniversityIndia 61 works
  5. 5 Saveetha UniversityIndia 52 works
  6. 6 Shanghai Jiao Tong UniversityChina 47 works
  7. 7 Southeast UniversityChina 47 works
  8. 8 South China University of TechnologyChina 43 works
  9. 9 Savitribai Phule Pune UniversityIndia 42 works
  10. 10 Chandigarh UniversityIndia 41 works

Who are the leading researchers in Emotion and Mood Recognition?

The most-cited researchers publishing on Emotion and Mood Recognition include Yoshua Bengio, Andrew Zisserman and Josep María Haro.

  1. 1 Yoshua Bengio Canada 476k citations
  2. 2 Andrew Zisserman United Kingdom 255k citations
  3. 3 Josep María Haro Spain 250k citations
  4. 4 Kai You Wang China 224k citations
  5. 5 Trevor J. Darrell United States 206k citations
  6. 6 Brenda W.J.H. Penninx Netherlands 190k citations
  7. 7 Luc Van Gool Switzerland 177k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Emotion and Mood Recognition?

The most cited paper in Emotion and Mood Recognition is "DEAP: A Database for Emotion Analysis ;Using Physiological Signals" (Sander Koelstra, Christian Mühl, Mohammad Soleymani et al., 2011), with 5,075 citations. Next come "The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression" (4,216) and "Patterns of cognitive appraisal in emotion." (3,889).

Most cited papers
#PaperReleasedCitations
1 DEAP: A Database for Emotion Analysis ;Using Physiological Signals Sander Koelstra, Christian Mühl, Mohammad Soleymani et al. · IEEE Transactions on Affective Computing Open access 17 Jun 2011 5,075
2 The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression Patrick J. Lucey, Jeffrey F. Cohn, Takeo Kanade et al. Conference paper Jun 2010 4,216
3 Patterns of cognitive appraisal in emotion. Craig A. Smith, Phoebe C. Ellsworth · Journal of Personality and Social Psychology 1985 3,889
4 IEMOCAP: interactive emotional dyadic motion capture database Carlos Busso, Murtaza Bulut, Chi-Chun Lee et al. · Language Resources and Evaluation 4 Nov 2008 3,844
5 A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions Zhihong Zeng, Maja Pantić, Glenn I. Roisman et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence 6 Nov 2008 2,807
All 100 most cited papers, with filters and sorting

Where is Emotion and Mood Recognition research done?

The largest centres of Emotion and Mood Recognition research in 2022-now are Beijing (China), Chennai (India), Shanghai (China) and Guangzhou (China). Among places with at least 20 works in it, it is an unusually large share of all research in Vijayawada and Greater Noida.

Largest cities, 2022-now

  1. 1 BeijingChina 452 works
  2. 2 ChennaiIndia 304 works
  3. 3 ShanghaiChina 207 works
  4. 4 GuangzhouChina 161 works
  5. 5 NanjingChina 148 works
  6. 6 PuneIndia 147 works
  7. 7 Xi'anChina 140 works
  8. 8 BengaluruIndia 139 works
  9. 9 TokyoJapan 137 works
  10. 10 CoimbatoreIndia 137 works

Where it is the local speciality

  1. VijayawadaIN · 53.5 works11×
  2. Greater NoidaIN · 57.0 works8.4×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Emotion and Mood Recognition than the world average.

See Emotion and Mood Recognition on the map

Where is the best place to study Emotion and Mood Recognition?

Among universities, judged by research, Nanyang Technological University, South China University of Technology and Hangzhou Dianzi University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 23.91%fractional works in this field (log) →share of work in the world top 10% →Nanyang Technologica…Hangzhou Dianzi Univ…South China Universi…Southeast University
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Nanyang Technological UniversitySingapore 77.930.6%3.2×24 +77.2%
2South China University of TechnologyChina 71.924.4%4.2×43 +171.7%
3Hangzhou Dianzi UniversityChina 71.727.7%8.2×26 +222.1%
4Southeast UniversityChina 66.016.4%3.4×47 +249.0%
5King Saud UniversitySaudi Arabia 65.723.7%1.5×14 +28.0%
6Lanzhou UniversityChina 65.324.2%4.0×26 +128.2%
7Shanghai Jiao Tong UniversityChina 64.616.1%1.8×47 +107.3%
8Beijing Institute of TechnologyChina 64.025.6%2.3×26 +140.3%
9University of MacauChina 63.824.8%3.0×9 +168.7%
10Fudan UniversityChina 63.025.6%1.5×22 +500.5%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Emotion and Mood Recognition, country by country

Is Emotion and Mood Recognition research growing?

Output in 2022-2025 was 132% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Emotion and Mood Recognition.

still counting19801990200020102020
grewheldshrank

The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Emotion and Mood Recognition as a percentage of every work published that year, 0.034% in 2024.

still counting0.020%0.040%0.060%Emotion and Mood Recognition0.059% in 202519801990200020102020

Fractional works of Emotion and Mood Recognition over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Emotion and Mood Recognition9.8% in 202520102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.

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