Open AccessBook
Social Network Analysis
Reads0
Chats0
TLDR
In this article, the development of social network analysis, tracing its origins in classical sociology and its more recent formulation in social scientific and mathematical work, is described and discussed. But it is argued that the analysis of social networks is not a purely static process.Abstract:
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...read more
Citations
More filters
Journal ArticleDOI
A measure of betweenness centrality based on random walks
TL;DR: In this paper, the authors propose a measure of betweenness based on random walks, counting how often a node is traversed by a random walk between two other nodes, not just the shortest paths.
Journal ArticleDOI
Evolution of the social network of scientific collaborations
Albert-László Barabási,Hawoong Jeong,Zoltán Néda,Zoltán Néda,Erzsébet Ravasz,András Schubert,Tamás Vicsek +6 more
TL;DR: In this paper, the authors analyzed the evolution of the co-authorship network of scientists and found that the network is scale-free and the network evolution is governed by preferential attachment, a8ecting both internal and external links.
Journal ArticleDOI
Mean-field theory for scale-free random networks
TL;DR: A mean-field method is developed to predict the growth dynamics of the individual vertices of the scale-free model, and this is used to calculate analytically the connectivity distribution and the scaling exponents.
Journal ArticleDOI
Hierarchical structure and the prediction of missing links in networks
TL;DR: This work presents a general technique for inferring hierarchical structure from network data and shows that the existence of hierarchy can simultaneously explain and quantitatively reproduce many commonly observed topological properties of networks.
Journal ArticleDOI
Characterization of complex networks: A survey of measurements
TL;DR: In this paper, the authors present a survey of topological features of complex networks, including trajectories in several measurement spaces, correlations between some of the most traditional measurements, perturbation analysis, as well as the use of multivariate statistics for feature selection and network classification.
References
More filters
Journal ArticleDOI
The Strength of Weak Ties
TL;DR: In this paper, it is argued that the degree of overlap of two individuals' friendship networks varies directly with the strength of their tie to one another, and the impact of this principle on diffusion of influence and information, mobility opportunity, and community organization is explored.
Journal ArticleDOI
Centrality in social networks conceptual clarification
TL;DR: In this article, three distinct intuitive notions of centrality are uncovered and existing measures are refined to embody these conceptions, and the implications of these measures for the experimental study of small groups are examined.
Journal ArticleDOI
Power and Centrality: A Family of Measures
TL;DR: In this article, the rank orderings by the four networks whose analysis forms the heart of this paper were analyzed and compared to the rank ordering by the three centrality measures, i.e., betweenness, nearness, and degree.
Journal ArticleDOI
Network data and measurement
TL;DR: Continued research on data quality is needed; beyond improved samples and further investigation of the informant accuracy/reliability issue, this should cover common indices of network structure, address the consequences of sampling portions of a network, and examine the robustness of indicators ofnetwork structure and position to both random and nonrandom errors of measurement.
Journal ArticleDOI
Social Structure from Multiple Networks. I. Blockmodels of Roles and Positions
TL;DR: In this paper, Boorman and White proposed a dual model that partitions a population while simultaneously identifying patterns of relations and role and position concepts in the concrete social structure of small populations.