Centrality in social networks conceptual clarification

doi:10.1016/0378-8733(78)90021-7

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Centrality in social networks conceptual clarification

Journal Article•DOI•

Centrality in social networks conceptual clarification

Linton C. Freeman¹•Institutions (1)

Lehigh University¹

01 Jan 1978-Social Networks (North-Holland)-Vol. 1, Iss: 3, pp 215-239

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.

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About: This article is published in Social Networks.The article was published on 1978-01-01 and is currently open access. It has received 14757 citations till now. The article focuses on the topics: Katz centrality & Random walk closeness centrality.

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Journal Article•DOI•

Complex network measures of brain connectivity: uses and interpretations.

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Mikail Rubinov¹, Olaf Sporns²•Institutions (2)

University of New South Wales¹, Indiana University²

01 Sep 2010-NeuroImage

TL;DR: Construction of brain networks from connectivity data is discussed and the most commonly used network measures of structural and functional connectivity are described, which variously detect functional integration and segregation, quantify centrality of individual brain regions or pathways, and test resilience of networks to insult.

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9,291 citations

Cites background from "Centrality in social networks conce..."

...Many measures of centrality are based on the idea that central nodes participate in many short paths within a network, and consequently act as important controls of information flow (Freeman, 1978)....
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...Betweenness centrality Betweenness centrality of node i (e.g., Freeman, 1978), bi = 1 n − 1ð Þ n − 2ð Þ P h; jaN h≠j;h≠i; j≠i; ρhj ið Þ ρhj ; where ρhj is the number of shortest paths between h and j, and ρhj (i) is the number of shortest paths between h and j that pass through i. Betweenness…...
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...…k w j lw δmi ;mj : Directed modularity (Leicht and Newman, 2008), QY = 1l P i;jaN aij − kouti k in i l δmi ;mj : Measures of centrality Closeness centrality Closeness centrality of node i (e.g. Freeman, 1978), L−1i = n − 1P jaN;j≠idij : Weighted closeness centrality, Lwi −1 = n − 1P jaN; j≠i dwij ....
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The igraph software package for complex network research

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Gábor Csárdi, Tamás Nepusz

01 Jan 2006

TL;DR: Platform-independent and open source igraph aims to satisfy all the requirements of a graph package while possibly remaining easy to use in interactive mode as well.

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Abstract: There is no other package around that satisfies all the following requirements: •Ability to handle large graphs efficiently •Embeddable into higher level environments (like R [6] or Python [7]) •Ability to be used for quick prototyping of new algorithms (impossible with “click & play” interfaces) •Platform-independent and open source igraph aims to satisfy all these requirements while possibly remaining easy to use in interactive mode as well.

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8,850 citations

Cites background from "Centrality in social networks conce..."

...Centrality measures The following centrality measures [7] can be calculated: • degree • closeness • vertex and edge betweenness • eigenvector centrality • page rank [12]....
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Journal Article•DOI•

Interorganizational Collaboration and the Locus of Innovation: Networks of Learning in Biotechnology.

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Walter W. Powell, Kenneth W. Koput, Laurel Smith-Doerr

01 Mar 1996-Administrative Science Quarterly

TL;DR: Powell et al. as mentioned in this paper developed a network approach to organizational learning and derive firm-level, longitudinal hypotheses that link research and development alliances, experience with managing interfirm relationships, network position, rates of growth, and portfolios of collaborative activities.

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Abstract: This research was supported by grants provided to the first author by the Social and Behavioral Sciences Research Institute, University of Arizona, and the Aspen Institute Nonprofit Sector Research Fund and by grants to the second author by the College of Business and Public Administration, University of Arizona. We have benefited from productive exchanges with numerous audiences to whom portions of this paper have been presented: a session at the 1994 Academy of Management meetings, the Social Organization workshop at the University of Arizona, the Work, Organizations, and Markets workshop at the Harvard Sociology Department, the 1994 SCOR Winter Conference at Stanford University, and colloquia at the business schools at the University of Alberta, UC-Berkeley, Duke, and Emory, and the JFK School at Harvard. For detailed comments on an earlier draft, we are extremely grateful to Victoria Alexander, Ashish Arora, Maryellen Kelley, Peter Marsden, Charles Kadushin, Dick Nelson, Christine Oliver, Lori Rosenkopf, Michael Sobel, Bill Starbuck, Art Stinchcombe, and anonymous reviewers at ASQ. We thank Dina Okamoto for research assistance and Linda Pike for editorial guidance. Address correspondence to Walter W. Powell, Department of Sociology, University of Arizona, Tucson, AZ 85721. We argue in this paper that when the knowledge base of an industry is both complex and expanding and the sources of expertise are widely dispersed, the locus of innovation will be found in networks of learning, rather than in individual firms. The large-scale reliance on interorganizational collaborations in the biotechnology industry reflects a fundamental and pervasive concern with access to knowledge. We develop a network approach to organizational learning and derive firm-level, longitudinal hypotheses that link research and development alliances, experience with managing interfirm relationships, network position, rates of growth, and portfolios of collaborative activities. We test these hypotheses on a sample of dedicated biotechnology firms in the years 1990-1994. Results from pooled, within-firm, time series analyses support a learning view and have broad implications for future theoretical and empirical research on organizational networks and strategic alliances.*

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8,249 citations

Book•

Social Network Analysis

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John Scott

30 Dec 1991

TL;DR: 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.

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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...

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6,366 citations

Journal Article•DOI•

Social Capital and Value Creation: The Role of Intrafirm Networks

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Wenpin Tsai¹, Sumantra Ghoshal²•Institutions (2)

Pennsylvania State University¹, London Business School²

01 Aug 1998-Academy of Management Journal

TL;DR: In this article, the relationships among the structural, relational, and cogni cation of a large multinational electronics company were examined using data collected from multiple respondents in all the business units of the company.

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Abstract: Using data collected from multiple respondents in all the business units of a large multinational electronics company, we examined the relationships both among the structural, relational, and cogni...

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5,621 citations

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References

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Journal Article•DOI•

A Set of Measures of Centrality Based on Betweenness

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Linton C. Freeman¹•Institutions (1)

Lehigh University¹

01 Mar 1977

TL;DR: A family of new measures of point and graph centrality based on early intuitions of Bavelas (1948) is introduced in this paper, which define centrality in terms of the degree to which a point falls on the shortest path between others and there fore has a potential for control of communication.

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Abstract: A family of new measures of point and graph centrality based on early intuitions of Bavelas (1948) is introduced. These measures define centrality in terms of the degree to which a point falls on the shortest path between others and there fore has a potential for control of communication. They may be used to index centrality in any large or small network of symmetrical relations, whether connected or unconnected.

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8,026 citations

Journal Article•DOI•

Optimum Locations of Switching Centers and the Absolute Centers and Medians of a Graph

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S. L. Hakimi¹•Institutions (1)

Northwestern University¹

01 Jun 1964-Operations Research

TL;DR: It is shown that the optimum location of a switching center is always at a vertex of the communication network while the best location for the police station is not necessarily at an intersection.

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Abstract: The concepts of the "center" and the "median vertex" of a graph are generalized to the "absolute center" and the "absolute median" of a weighted graph a graph with weights attached to its vertices as well as to its branches. These results are used to find the optimum location of a "switching center" in a communication network and to locate the best place to build a "police station" in a highway system. It is shown that the optimum location of a switching center is always at a vertex of the communication network while the best location for the police station is not necessarily at an intersection. Procedures for finding these locations are given.

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2,224 citations

Journal Article•DOI•

The centrality index of a graph

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Gert Sabidussi¹•Institutions (1)

McMaster University¹

01 Dec 1966-Psychometrika

2,136 citations

"Centrality in social networks conce..." refers background in this paper

...It has been expressed in one form or another by Bavelas (1950), Flament Centrality in social networks 227 (1963), Beauchamp (1965) and Sabidussi (1966)....
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...Hakimi (1965) and Sabidussi (1966) made it completely general when they defined the most central point in a network as that with the minimum cost or time for communicating with all other points....
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...Closeness-based measures of point centrality have been developed by Bavelas (1950), Beauchamp (1965), Sabidussi (1966), Moxley and Moxley (1974) and Rogers (1974)....
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...Sabidussi (1966) showed that this conjecture was wrong, but did not provide an alternative interpretation....
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Journal Article•DOI•

Communication Patterns in Task‐Oriented Groups

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Alex Bavelas¹•Institutions (1)

Massachusetts Institute of Technology¹

01 Nov 1950-Journal of the Acoustical Society of America

1,874 citations

"Centrality in social networks conce..." refers background in this paper

...According to Bavelas (1950), a non-central position is one that “must relay messages through . . . others”....
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...It has been expressed in one form or another by Bavelas (1950), Flament Centrality in social networks 227 (1963), Beauchamp (1965) and Sabidussi (1966)....
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...Closeness-based measures of point centrality have been developed by Bavelas (1950), Beauchamp (1965), Sabidussi (1966), Moxley and Moxley (1974) and Rogers (1974)....
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...They were reported by Bavelas (1950) and Bavelas and Barrett (195 l), and were first described in detail by Leavitt (195 1)....
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