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Social network analysis

Social network analysis

Cronin, Bruce (2016) Social network analysis. In: Lee, Frederic and Cronin, Bruce, (eds.) Handbook of Research Methods and Applications in Heterodox Economics. Handbooks of Research Methods and Applications . Edward Elgar, Cheltenham, UK, pp. 237-252. ISBN 9781782548454 (doi:10.4337/9781782548461)

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Abstract

Social network analysis comprises a powerful set of techniques for quantifying, differentiating, and interpreting social interactions or relational data in general. This provides a means of interrogating assumptions of independent yet homogeneous actions and pay-offs in economic processes, a particular interest of heterodox approaches to economics. Contemporary applications include modelling opinion leadership among consumers, search and matching in labour markets, collaboration in research and development, patterns of innovation diffusion among firms, and global commodity chains.

This chapter introduces the central concepts and methods of social network analysis, including data collection and interpretation considerations and a brief discussion of specialized software in the field. Each is illustrated with an economic application, either a heterodox example or with a discussion of its heterodox implications.

Item Type: Book Section
Additional Information: This draft chapter has been published by Edward Elgar Publishing in Handbook of Research Methods and Applications in Heterodox Economics edited by Frederick S. Lee and Bruce Cronin published in 2016. http://www.elgaronline.com/view/9781782548454.xml
Uncontrolled Keywords: Social network, Analysis, Heterodox economics
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HA Statistics
H Social Sciences > HB Economic Theory
H Social Sciences > HM Sociology
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Centre for Business Network Analysis
Faculty of Business > Department of International Business & Economics
Last Modified: 30 Oct 2016 00:38
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/14972

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