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Topic · Computer Science Applications

Mobile Crowdsensing and Crowdsourcing

Mobile Crowdsensing and Crowdsourcing is a research topic within Computer Science Applications. Science Explorer counts 14k research works in it since 1972. 9.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the use of crowdsourcing platforms, particularly Amazon's Mechanical Turk, for research and data collection purposes. It explores topics such as data quality, incentive mechanisms, mobile sensing, truth discovery, and the application of crowdsourcing in behavioral research and participatory sensing.

  • Crowdsourcing
  • Mechanical Turk
  • Mobile Sensing
  • Data Quality
  • Incentive Mechanisms
  • Online Labor Markets
  • Behavioral Research
  • Participatory Sensing
  • Truth Discovery
  • Social Networks
Research works
14k
fractional, since 1972
In the world top 10%
1.4k
per year above
Top-10% rate
9.9%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
-9%
the tick is no change
Largest producer
China
40% of the 10 largest, 2022-now
Mobile Crowdsensing and Crowdsourcing

Which countries lead Mobile Crowdsensing and Crowdsourcing research?

By volume, China and the United States publish the most (1.2k and 756 works in 2022-now).

By volume, 2022-now

  1. 1 China 1.2k works
  2. 2 United States 756 works
  3. 3 India 245 works
  4. 4 Germany 160 works
  5. 5 United Kingdom 149 works
  6. 6 Japan 119 works
  7. 7 Italy 114 works
  8. 8 Canada 105 works
  9. 9 Australia 104 works
  10. 10 France 68 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: 40.3%United States: 24.8%India: 8.0%Germany: 5.3%6 others listed: 21.6%40%largest
China1,227 · 40.3%United States756 · 24.8%India245 · 8.0%Germany160 · 5.3%6 others listed658 · 21.6%

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

Which institutions lead Mobile Crowdsensing and Crowdsourcing research?

By volume in 2022-now, Chinese Academy of Sciences publishes the most Mobile Crowdsensing and Crowdsourcing research, followed by Beijing University of Posts and Telecommunications and Carnegie Mellon University.

By volume, 2022-now

  1. 1 Chinese Academy of SciencesChina 32 works
  2. 2 Beijing University of Posts and TelecommunicationsChina 29 works
  3. 3 Carnegie Mellon UniversityUnited States 25 works
  4. 4 University of Science and Technology of ChinaChina 22 works
  5. 5 Tsinghua UniversityChina 21 works
  6. 6 Shanghai Jiao Tong UniversityChina 20 works
  7. 7 Beijing Institute of TechnologyChina 19 works
  8. 8 Nanyang Technological UniversitySingapore 19 works
  9. 9 National University of Defense TechnologyChina 18 works
  10. 10 Centre National de la Recherche ScientifiqueFrance 18 works

Who are the leading researchers in Mobile Crowdsensing and Crowdsourcing?

The most-cited researchers publishing on Mobile Crowdsensing and Crowdsourcing include Yoshua Bengio, Rob Knight and Isabelle Boutron.

  1. 1 Yoshua Bengio Canada 476k citations
  2. 2 Rob Knight United States 468k citations
  3. 3 Isabelle Boutron France 271k citations
  4. 4 Li Fei-Fei United States 225k citations
  5. 5 Kai You Wang China 224k 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 Mobile Crowdsensing and Crowdsourcing?

The most cited paper in Mobile Crowdsensing and Crowdsourcing is "Internet of Things (IoT): A vision, architectural elements, and future directions" (Jayavardhana Gubbi, Rajkumar Buyya, Slaven Marusic et al., 2013), with 12,285 citations. Next come "Fog computing and its role in the internet of things" (6,098) and "From Louvain to Leiden: guaranteeing well-connected communities" (5,618).

Most cited papers
#PaperReleasedCitations
1 Internet of Things (IoT): A vision, architectural elements, and future directions Jayavardhana Gubbi, Rajkumar Buyya, Slaven Marusic et al. · Future Generation Computer Systems Open access 24 Feb 2013 12,285
2 Fog computing and its role in the internet of things Flavio Bonomi, Rodolfo A. Milito, Jiang Zhu et al. Conference paperOpen access 17 Aug 2012 6,098
3 From Louvain to Leiden: guaranteeing well-connected communities V. A. Traag, L. Waltman, Nees Jan van Eck · Scientific Reports Open access 26 Mar 2019 5,618
4 Advances and Open Problems in Federated Learning Peter Kairouz et al. · Foundations and Trends® in Machine Learning Open access 2 Dec 2020 5,510
5 Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk Adam J. Berinsky, Gregory A. Huber, Gabriel Lenz · Political Analysis Open access 2012 4,118
All 99 most cited papers, with filters and sorting

Where is Mobile Crowdsensing and Crowdsourcing research done?

The largest centres of Mobile Crowdsensing and Crowdsourcing research in 2022-now are Beijing (China), Nanjing (China), Shanghai (China) and Xi'an (China). Among places with at least 20 works in it, it is an unusually large share of all research in Pittsburgh.

Largest cities, 2022-now

  1. 1 BeijingChina 222 works
  2. 2 NanjingChina 78 works
  3. 3 ShanghaiChina 77 works
  4. 4 Xi'anChina 65 works
  5. 5 GuangzhouChina 62 works
  6. 6 WuhanChina 56 works
  7. 7 Hong KongChina 52 works
  8. 8 ChangshaChina 51 works
  9. 9 TokyoJapan 49 works
  10. 10 HangzhouChina 49 works

Where it is the local speciality

  1. PittsburghUS · 29.2 works4.4×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Mobile Crowdsensing and Crowdsourcing than the world average.

See Mobile Crowdsensing and Crowdsourcing on the map

Where is the best place to study Mobile Crowdsensing and Crowdsourcing?

Among universities, judged by research, Hong Kong Polytechnic University, Carnegie Mellon University and Nanyang Technological 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 18.25%fractional works in this field (log) →share of work in the world top 10% →Jinan UniversityHong Kong Polytechni…Nanyang Technologica…Carnegie Mellon Univ…
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
1Hong Kong Polytechnic UniversityChina 70.222.7%5.2×15 +75.4%
2Carnegie Mellon UniversityUnited States 64.419.8%17.7×25 -36.8%
3Nanyang Technological UniversitySingapore 63.020.1%7.2×19 -6.2%
4Jinan UniversityChina 59.530.5%4.7×9 +346.3%
5City University of Hong KongChina 58.220.6%5.5×11 +15.5%
6Beijing University of Posts and TelecommunicationsChina 57.611.6%13.4×29 -5.4%
7Beijing Institute of TechnologyChina 55.010.8%4.9×20 +28.3%
8University of Science and Technology of ChinaChina 54.112.1%5.5×22 +7.1%
9Central South UniversityChina 50.818.1%2.2×14 +16.9%
10Tsinghua UniversityChina 48.216.2%2.7×21 -20.9%

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 Mobile Crowdsensing and Crowdsourcing, country by country

Is Mobile Crowdsensing and Crowdsourcing research growing?

Output in 2022-2025 was 9% lower than in 2018-2021, peaking in 2022.

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 Mobile Crowdsensing and Crowdsourcing as a percentage of every work published that year, 0.012% in 2024.

still counting0.010%0.020%0.030%Mobile Crowdsensing and Crowdsourcing0.014% in 202519801990200020102020

Fractional works of Mobile Crowdsensing and Crowdsourcing 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%Mobile Crowdsensing and Crowdsourcing10.0% 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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