Estimating point centrality using different network sampling techniques

Joseph Galaskiewicz

doi:10.1016/0378-8733(91)90002-B

Estimating point centrality using different network sampling techniques

Joseph Galaskiewicz

Research output: Contribution to journal › Article › peer-review

39 Scopus citations

Abstract

The paper outlines the methodological choices that analysts must make when sampling social networks and assesses the impact of different sampling techniques on the estimation of network parameters. Using data from Galaskiewicz's (1919) study of Towertown and River City, the results show the extent to which sampling percentage, the number of trials/estimates, sampling procedure, and network size and density affect the ability of researchers to estimate the point centrality of organizations in networks of information and money transactions.

Original language	English (US)
Pages (from-to)	347-386
Number of pages	40
Journal	Social Networks
Volume	13
Issue number	4
DOIs	https://doi.org/10.1016/0378-8733(91)90002-B
State	Published - Dec 1991
Externally published	Yes

ASJC Scopus subject areas

Anthropology
Sociology and Political Science
General Social Sciences
General Psychology

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10.1016/0378-8733(91)90002-B

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title = "Estimating point centrality using different network sampling techniques",

abstract = "The paper outlines the methodological choices that analysts must make when sampling social networks and assesses the impact of different sampling techniques on the estimation of network parameters. Using data from Galaskiewicz's (1919) study of Towertown and River City, the results show the extent to which sampling percentage, the number of trials/estimates, sampling procedure, and network size and density affect the ability of researchers to estimate the point centrality of organizations in networks of information and money transactions.",

author = "Joseph Galaskiewicz",

note = "Funding Information: Funding for this paper was provided by the National Science Foundation (SOC73-13113 and SOCSS-87258) and the University of Minnesota. Special thanks to Hilda Daniels for helping to prepare the graphs and figures and to Thomas Schott and Mark Granovetter for reading and commenting on an earlier draft of the paper.",

year = "1991",

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doi = "10.1016/0378-8733(91)90002-B",

language = "English (US)",

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journal = "Social Networks",

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publisher = "Elsevier B.V.",

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AU - Galaskiewicz, Joseph

N1 - Funding Information: Funding for this paper was provided by the National Science Foundation (SOC73-13113 and SOCSS-87258) and the University of Minnesota. Special thanks to Hilda Daniels for helping to prepare the graphs and figures and to Thomas Schott and Mark Granovetter for reading and commenting on an earlier draft of the paper.

PY - 1991/12

Y1 - 1991/12

N2 - The paper outlines the methodological choices that analysts must make when sampling social networks and assesses the impact of different sampling techniques on the estimation of network parameters. Using data from Galaskiewicz's (1919) study of Towertown and River City, the results show the extent to which sampling percentage, the number of trials/estimates, sampling procedure, and network size and density affect the ability of researchers to estimate the point centrality of organizations in networks of information and money transactions.

AB - The paper outlines the methodological choices that analysts must make when sampling social networks and assesses the impact of different sampling techniques on the estimation of network parameters. Using data from Galaskiewicz's (1919) study of Towertown and River City, the results show the extent to which sampling percentage, the number of trials/estimates, sampling procedure, and network size and density affect the ability of researchers to estimate the point centrality of organizations in networks of information and money transactions.

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U2 - 10.1016/0378-8733(91)90002-B

DO - 10.1016/0378-8733(91)90002-B

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VL - 13

SP - 347

EP - 386

JO - Social Networks

JF - Social Networks

IS - 4

ER -

Estimating point centrality using different network sampling techniques

Abstract

ASJC Scopus subject areas

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