Journal ArticleDOI
Scientific collaboration networks. I. Network construction and fundamental results.
Mark Newman,Mark Newman +1 more
Reads0
Chats0
TLDR
Using computer databases of scientific papers in physics, biomedical research, and computer science, a network of collaboration between scientists in each of these disciplines is constructed, and a number of measures of centrality and connectedness in the same networks are studied.Abstract:
Using computer databases of scientific papers in physics, biomedical research, and computer science, we have constructed networks of collaboration between scientists in each of these disciplines. In these networks two scientists are considered connected if they have coauthored one or more papers together. We study a variety of statistical properties of our networks, including numbers of papers written by authors, numbers of authors per paper, numbers of collaborators that scientists have, existence and size of a giant component of connected scientists, and degree of clustering in the networks. We also highlight some apparent differences in collaboration patterns between the subjects studied. In the following paper, we study a number of measures of centrality and connectedness in the same networks.read more
Citations
More filters
Journal ArticleDOI
Statistical mechanics of complex networks
TL;DR: In this paper, a simple model based on the power-law degree distribution of real networks was proposed, which was able to reproduce the power law degree distribution in real networks and to capture the evolution of networks, not just their static topology.
Journal ArticleDOI
The Structure and Function of Complex Networks
TL;DR: Developments in this field are reviewed, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
Journal ArticleDOI
Community structure in social and biological networks
Michelle Girvan,Mark Newman +1 more
TL;DR: This article proposes a method for detecting communities, built around the idea of using centrality indices to find community boundaries, and tests it on computer-generated and real-world graphs whose community structure is already known and finds that the method detects this known structure with high sensitivity and reliability.
Journal ArticleDOI
Complex networks: Structure and dynamics
TL;DR: The major concepts and results recently achieved in the study of the structure and dynamics of complex networks are reviewed, and the relevant applications of these ideas in many different disciplines are summarized, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.
Journal ArticleDOI
Statistical physics of social dynamics
TL;DR: In this article, a wide list of topics ranging from opinion and cultural and language dynamics to crowd behavior, hierarchy formation, human dynamics, and social spreading are reviewed and connections between these problems and other, more traditional, topics of statistical physics are highlighted.
References
More filters
Book
Social Network Analysis: A Handbook
TL;DR: Networks and Relations The Development of Social Network Analysis Handling Relational Data Lines, Direction and Density Centrality and Centralization Components, Cores, and Cliques Positions, Roles and Clusters Dimensions and Displays Appendix Social Network Packages
国际刊物《Scientometrics》文献计量研究
TL;DR: In this paper, the authors propose a method to improve the quality of the data collected by the data collection system. But it is difficult to implement and time consuming and computationally expensive.