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Topic Modeling

Topic Modeling is a research topic within Artificial Intelligence. Science Explorer counts 73k research works in it since 1956. 9.6% of them reached the world's top 10% most cited for their field and year.

This cluster of papers covers a wide range of advancements in natural language processing, including neural network architectures, word representation models, machine translation techniques, text classification algorithms, semantic similarity measures, named entity recognition methods, pretrained language models, sequence-to-sequence learning approaches, topic modeling strategies, and information retrieval systems.

  • Neural Networks
  • Word Representation
  • Machine Translation
  • Text Classification
  • Semantic Similarity
  • Named Entity Recognition
  • Pretrained Models
  • Sequence-to-Sequence Learning
  • Topic Modeling
  • Information Retrieval
Research works
73k
fractional, since 1956
In the world top 10%
6.9k
per year above
Top-10% rate
9.6%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+65%
the tick is no change
Largest producer
China
44% of the 10 largest, 2022-now
Topic Modeling

Which countries lead Topic Modeling research?

By volume, China and the United States publish the most (10k and 5k works in 2022-now).

By volume, 2022-now

  1. 1 China 10k works
  2. 2 United States 5k works
  3. 3 India 2.6k works
  4. 4 Germany 1.1k works
  5. 5 United Kingdom 1k works
  6. 6 Japan 812 works
  7. 7 South Korea 649 works
  8. 8 Canada 622 works
  9. 9 Italy 535 works
  10. 10 France 516 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: 43.8%United States: 22.0%India: 11.4%Germany: 4.7%6 others listed: 18.2%44%largest
China10k · 43.8%United States5,023 · 22.0%India2,602 · 11.4%Germany1,078 · 4.7%6 others listed4,150 · 18.2%

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

Which institutions lead Topic Modeling research?

By volume in 2022-now, Chinese Academy of Sciences publishes the most Topic Modeling research, followed by Tsinghua University and Peking University.

By volume, 2022-now

  1. 1 Chinese Academy of SciencesChina 405 works
  2. 2 Tsinghua UniversityChina 216 works
  3. 3 Peking UniversityChina 191 works
  4. 4 Beijing University of Posts and TelecommunicationsChina 187 works
  5. 5 National University of Defense TechnologyChina 171 works
  6. 6 Microsoft (United States)United States 171 works
  7. 7 Shanghai Jiao Tong UniversityChina 163 works
  8. 8 Centre National de la Recherche ScientifiqueFrance 162 works
  9. 9 Harbin Institute of TechnologyChina 162 works
  10. 10 University of Science and Technology of ChinaChina 149 works

Who are the leading researchers in Topic Modeling?

The most-cited researchers publishing on Topic Modeling include Kaiming He, Yoshua Bengio and Geoffrey E. Hinton.

  1. 1 Kaiming He Israel 562k citations
  2. 2 Yoshua Bengio Canada 476k citations
  3. 3 Geoffrey E. Hinton Canada 454k citations
  4. 4 Julian P. T. Higgins United Kingdom 390k citations
  5. 5 Xiangyu Zhang 327k citations
  6. 6 Dan J. Stein South Africa 306k 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 Topic Modeling?

The most cited paper in Topic Modeling is "Exploiting Generative AI to Scale up Intelligent Tutoring Systems" (Jakubův, Jan, Chvalovský, Karel, Goertzel, Zarathustra et al., 2023), with 79,061 citations. Next come "AI-Assisted Pipeline for Dynamic Generation of Trustworthy Health Supplement Content at Scale" (46,030) and "Glove: Global Vectors for Word Representation" (34,197).

Most cited papers
#PaperReleasedCitations
1 Exploiting Generative AI to Scale up Intelligent Tutoring Systems Jakubův, Jan, Chvalovský, Karel, Goertzel, Zarathustra et al. · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) Open access 2023 79,061
2 AI-Assisted Pipeline for Dynamic Generation of Trustworthy Health Supplement Content at Scale Kefallinos, Dionysios, Alexandris, Georgios, Maras, Alexis et al. · arXiv (Cornell University) PreprintOpen access 11 Oct 2018 46,030
3 Glove: Global Vectors for Word Representation Jeffrey Pennington, Richard Socher, Christopher D. Manning Conference paper 2014 34,197
4 Latent dirichlet allocation David M. Blei, Andrew Y. Ng, Michael I. Jordan · Journal of Machine Learning Research Mar 2003 27,026
5 Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation Kyunghyun Cho, Bart van Merriënboer, Çağlar Gülçehre et al. Conference paperOpen access 2014 25,290
All 94 most cited papers, with filters and sorting

Where is Topic Modeling research done?

The largest centres of Topic Modeling research in 2022-now are Beijing (China), Shanghai (China), Guangzhou (China) and Hangzhou (China). Among places with at least 20 works in it, it is an unusually large share of all research in Redmond, San Mateo and Nomi Shi.

Largest cities, 2022-now

  1. 1 BeijingChina 2.4k works
  2. 2 ShanghaiChina 766 works
  3. 3 GuangzhouChina 437 works
  4. 4 HangzhouChina 420 works
  5. 5 WuhanChina 417 works
  6. 6 NanjingChina 393 works
  7. 7 SeoulSouth Korea 385 works
  8. 8 TokyoJapan 364 works
  9. 9 ShenzhenChina 357 works
  10. 10 SingaporeSingapore 341 works

Where it is the local speciality

  1. RedmondUS · 54.5 works19×
  2. San MateoUS · 31.3 works19×
  3. Nomi ShiJP · 29.5 works15×
  4. IkomaJP · 23.4 works10×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Topic Modeling than the world average.

See Topic Modeling on the map

Where is the best place to study Topic Modeling?

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

0%10%20%30%mean 19.07%fractional works in this field (log) →share of work in the world top 10% →University of Hong K…Nanyang Technologica…Stanford UniversityNational 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.

Citation 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 82.022.1%5.2×106 +45.5%
2University of Hong KongChina 79.825.5%2.9×70 +247.9%
3Stanford UniversityUnited States 79.220.6%2.6×98 +17.3%
4National University of SingaporeSingapore 75.918.0%3.5×106 +104.3%
5Tsinghua UniversityChina 74.815.8%3.6×216 +25.0%
6University of WashingtonUnited States 74.722.8%2.3×67 +26.6%
7Singapore Management UniversitySingapore 73.519.3%17.9×49 +85.3%
8Hong Kong University of Science and TechnologyChina 71.415.6%7.1×76 +60.2%
9University of Illinois Urbana-ChampaignUnited States 69.813.0%5.3×118 +53.8%
10Hong Kong Polytechnic UniversityChina 69.618.0%3.7×82 +141.1%

Universities only. The score blends citation 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 Topic Modeling, country by country

Is Topic Modeling research growing?

Output in 2022-2025 was 65% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Topic Modeling.

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 Topic Modeling as a percentage of every work published that year, 0.12% in 2024.

still counting0.050%0.10%0.15%Topic Modeling0.14% in 202519801990200020102020

Fractional works of Topic Modeling 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%Topic Modeling9.5% in 2025200020102020

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.

Discussion

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