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. 35.7% 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%
- 4.9k per year above
- Top-10% rate
- 35.7% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +20% the tick is no change
Which countries lead Mobile Crowdsensing and Crowdsourcing research?
By volume, China and the United States publish the most (970 and 605 works in 2022–2025).
By volume, 2022–2025
- 1 China 970 works
- 2 United States 605 works
- 3 India 176 works
- 4 Germany 139 works
- 5 United Kingdom 130 works
- 6 Japan 102 works
- 7 Italy 101 works
- 8 Canada 91 works
- 9 Australia 89 works
- 10 France 58 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.
Shares of the rows listed above, not of the whole node.
Which institutions lead Mobile Crowdsensing and Crowdsourcing research?
By volume in 2022–2025, Beijing University of Posts and Telecommunications publishes the most Mobile Crowdsensing and Crowdsourcing research, followed by Carnegie Mellon University and University of Science and Technology of China.
By volume, 2022–2025
- 1 Beijing University of Posts and TelecommunicationsChina 24 works
- 2 Carnegie Mellon UniversityUnited States 20 works
- 3 University of Science and Technology of ChinaChina 19 works
- 4 Tsinghua UniversityChina 19 works
- 5 Shanghai Jiao Tong UniversityChina 18 works
- 6 Beijing Institute of TechnologyChina 16 works
- 7 National University of Defense TechnologyChina 16 works
- 8 Northwestern Polytechnical UniversityChina 16 works
- 9 Delft University of TechnologyNetherlands 16 works
- 10 Nanyang Technological UniversitySingapore 15 works
Who are the leading researchers in Mobile Crowdsensing and Crowdsourcing?
The most-cited researchers publishing on Mobile Crowdsensing and Crowdsourcing include Serge Belongie, Michael S. Bernstein and Rajkumar Buyya.
- 1 Serge Belongie United States 14k citations
- 2 Michael S. Bernstein United States 10k citations
- 3 Rajkumar Buyya Australia 7.8k citations
- 4 Philip S. Yu United States 6.6k citations
- 5 Deborah Estrin United States 5.9k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Mobile Crowdsensing and Crowdsourcing research done?
The largest centres of Mobile Crowdsensing and Crowdsourcing research in 2022–2025 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 and Hong Kong.
Largest cities, 2022–2025
Where it is the local speciality
- PittsburghUS · 25.0 works4.6×
- Hong KongCN · 43.6 works4.2×
Location quotient: how much more of its research is in Mobile Crowdsensing and Crowdsourcing than the world average.
Where is the best place to study Mobile Crowdsensing and Crowdsourcing?
Among universities, judged by research, Beijing University of Posts and Telecommunications, 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.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Beijing University of Posts and TelecommunicationsChina | 74.3 | 33.2% | 12.5× | 24 | +277.8% |
| 2 | Carnegie Mellon UniversityUnited States | 67.8 | 44.9% | 15.8× | 20 | -11.5% |
| 3 | Nanyang Technological UniversitySingapore | 63.4 | 47.8% | 6.2× | 16 | +47.8% |
| 4 | Hong Kong University of Science and TechnologyHong Kong | 63.0 | 29.8% | 10.9× | 13 | +113.1% |
| 5 | Delft University of TechnologyNetherlands | 57.6 | 38.3% | 7.5× | 16 | +44.9% |
| 6 | City University of Hong KongHong Kong | 56.5 | 53.7% | 4.6× | 8 | +85.0% |
| 7 | University of Science and Technology of ChinaChina | 55.0 | 30.1% | 5.1× | 19 | +336.9% |
| 8 | Hong Kong Polytechnic UniversityHong Kong | 51.9 | 36.8% | 4.7× | 13 | +96.4% |
| 9 | Beijing Institute of TechnologyChina | 51.4 | 32.6% | 4.4× | 16 | +791.1% |
| 10 | University of Electronic Science and Technology of ChinaChina | 51.1 | 34.4% | 4.2× | 15 | +252.8% |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Mobile Crowdsensing and Crowdsourcing research growing?
Output in 2018–2022 was 20% higher than in 2013–2017, peaking in 2022. The fastest-growing topics are Mobile Crowdsensing and Crowdsourcing.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
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.