The structure of scientific collaboration networks.
@article{Newman2001TheSO, title={The structure of scientific collaboration networks.}, author={Mark E. J. Newman}, journal={Proceedings of the National Academy of Sciences of the United States of America}, year={2001}, volume={98 2}, pages={ 404-9 } }
The structure of scientific collaboration networks is investigated. Two scientists are considered connected if they have authored a paper together and explicit networks of such connections are constructed by using data drawn from a number of databases, including MEDLINE (biomedical research), the Los Alamos e-Print Archive (physics), and NCSTRL (computer science). I show that these collaboration networks form "small worlds," in which randomly chosen pairs of scientists are typically separated…
4,254 Citations
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References
SHOWING 1-10 OF 54 REFERENCES
Emergence of scaling in random networks
- Computer ScienceScience
- 1999
A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
A portion of the well-known collaboration graph
- Mathematics
- 1995
An on-going project in which a portion of this graph—in particular, a list of all people with small Erdős numbers—is made available in electronic form is reported on.
Collective dynamics of ‘small-world’ networks
- Computer ScienceNature
- 1998
Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Small worlds
- Computer Science, MathematicsRandom Struct. Algorithms
- 2001
This paper considers some particular instances of small world models, and rigorously investigates the distribution of their inter‐point network distances, framed in terms of approximations, whose accuracy increases with the size of the network.
Social Network Analysis
- Economics
- 1988
This paper reports on the development of social network analysis, tracing its origins in classical sociology and its more recent formulation in social scientific and mathematical work. It is argued…
Random graphs with arbitrary degree distributions and their applications.
- MathematicsPhysical review. E, Statistical, nonlinear, and soft matter physics
- 2001
It is demonstrated that in some cases random graphs with appropriate distributions of vertex degree predict with surprising accuracy the behavior of the real world, while in others there is a measurable discrepancy between theory and reality, perhaps indicating the presence of additional social structure in the network that is not captured by the random graph.
Social Cohesion and Embeddedness : A Hierarchical Conception of Social Groups
- Economics
- 2000
SFI WORKING PAPER: 2000-08-049 SFI Working Papers contain accounts of scientific work of the author(s) and do not necessarily represent the views of the Santa Fe Institute. We accept papers intended…
Internet: Diameter of the World-Wide Web
- Computer ScienceNature
- 1999
The World-Wide Web becomes a large directed graph whose vertices are documents and whose edges are links that point from one document to another, which determines the web's connectivity and consequently how effectively the authors can locate information on it.
Structural cohesion and embeddedness: A hierarchical concept of social groups
- Geology
- 2003
While questions about social cohesion lie at the core of our discipline, no clear definition of cohesion exists. We present a definition of structural cohesion based on network connectivity that…