Social Capital and Networks
Social Capital and Networks is a research topic within Sociology and Political Science. Science Explorer counts 14k research works in it since 1950. 10.2% of them reached the world's top 10% most cited for their field and year.
This cluster of papers explores the concept of social capital, trust, and community networks, examining their implications for civic engagement, inequality, diversity, and economic development. It delves into the role of social capital in fostering social cohesion and building civil society, with a focus on the impact of trust on various aspects of community life.
- Social Capital
- Trust
- Community
- Networks
- Civic Engagement
- Inequality
- Diversity
- Civil Society
- Economic Development
- Social Cohesion
- Research works
- 14k fractional, since 1950
- In the world top 10%
- 1.4k per year above
- Top-10% rate
- 10.2% share of its works in the world top 10%
- Growth, 2018-21 → 2022-25
- -5% the tick is no change
- Largest producer
United States
31% of the 10 largest, 2022-now
Which countries lead Social Capital and Networks research?
By volume, the United States and China publish the most (498 and 398 works in 2022-now).
By volume, 2022-now
- 1
United States 498 works
- 2
China 398 works
- 3
United Kingdom 146 works
- 4
Germany 136 works
- 5
Italy 87 works
- 6
Indonesia 82 works
- 7
Netherlands 62 works
- 8
Spain 60 works
- 9
Canada 59 works
- 10
Türkiye 59 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 Social Capital and Networks research?
By volume in 2022-now, Renmin University of China publishes the most Social Capital and Networks research, followed by Centre National de la Recherche Scientifique and Duke University.
By volume, 2022-now
- 1
Renmin University of China
China 12 works
- 2
Centre National de la Recherche Scientifique
France 11 works
- 3
Duke University
United States 10 works
- 4
Fudan University
China 10 works
- 5
Islamic Azad University, Tehran
Iran 10 works
- 6
Sapienza University of Rome
Italy 9 works
- 7
University of Chicago
United States 9 works
- 8
Indiana University
United States 9 works
- 9
Leibniz Association
Germany 9 works
- 10
Peking University
China 9 works
Who are the leading researchers in Social Capital and Networks?
The most-cited researchers publishing on Social Capital and Networks include Ronald C. Kessler, Mika Kivimäki and Martin McKee.
- 1
Ronald C. Kessler
United States 360k citations
- 2
Mika Kivimäki
United Kingdom 318k citations
- 3
Martin McKee
United Kingdom 270k citations
- 4
Pierre Bourdıeu
France 268k citations
- 5
Josep María Haro
Spain 250k citations
- 6
Azeem Majeed
United Kingdom 235k citations
- 7
Andrei Shleifer
United States 234k citations
- 8
Albert-Ĺaszló Barabási
United States 223k citations
- 9
Norito Kawakami
Japan 202k citations
- 10
Harry Eugene Stanley
United States 198k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Social Capital and Networks research done?
The largest centres of Social Capital and Networks research in 2022-now are Beijing (China), Shanghai (China), London (United Kingdom) and Moscow (Russia).
Where is the best place to study Social Capital and Networks?
Among universities, judged by research, Renmin University of China, Duke University and Stanford 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 first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Renmin University of China |
75.5 | 14.5% | 16.2× | 12 | +37.7% |
| 2 | Duke University |
64.1 | 3.4% | 5.6× | 10 | +76.6% |
| 3 | Stanford University |
62.5 | 18.5% | 2.5× | 8 | +25.2% |
| 4 | University of Chicago |
62.1 | 13.3% | 4.7× | 9 | +87.4% |
| 5 | Sapienza University of Rome |
57.5 | 20.1% | 3.5× | 9 | +203.8% |
| 6 | Chongqing University |
56.1 | 26.3% | 3.4× | 8 | +191.9% |
| 7 | Fudan University |
53.2 | 14.0% | 2.8× | 10 | +60.8% |
| 8 | Peking University |
42.6 | 11.0% | 1.9× | 9 | +96.7% |
| 9 | Michigan State University |
37.8 | 8.1% | 5.0× | 8 | -13.0% |
| 10 | Indiana University |
34.8 | 9.0% | 4.1× | 9 | -52.3% |
| 11 | National Research University Higher School of Economics |
26.7 | 5.4% | 9.6× | 9 | -48.1% |
| 12 | Islamic Azad University, Tehran |
14.9 | 0.4% | 2.6× | 10 | -49.0% |
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 Social Capital and Networks, country by countryIs Social Capital and Networks research growing?
Output in 2022-2025 was 5% lower than in 2018-2021, peaking in 2015.
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 Social Capital and Networks as a percentage of every work published that year, 0.0088% in 2024.
Fractional works of Social Capital and Networks 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.
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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