Readings

People often ask what they should read before coming to the workshop. Here are a few suggestions, organized by module. You may also want to look at the reading list for Borgatti's PhD course.

Introduction to SNA

    • Borgatti, S.P. and Foster, P. 2003. The network paradigm in organizational research: A review and typology. Journal of Management. 29(6): 991-1013 [pdf]

    • Borgatti, S.P., Mehra, A., Brass, D. and Labianca, G. (2009). “Network Analysis in the Social Sciences.” Science. Vol. 323. no. 5916, Feb 13, pp. 892 - 895 [abs] [published version] [longer pre-pub version]

    • Kilduff, M. and Brass, D. (2010). Organizational social network research: Core ideas and key debates. Academy of Management Annuals. Vol. 4, 317-357. Routledge. [pdf]

    • Brass, D. (forthcoming). A social network perspective on industrial/organizational psychology. Industrial/Organizational Handbook. [pdf]

    • UCINET Quick-Start Guide [pdf]

Analyzing SNA Data

    • Borgatti, SP, Everett, MG & Johnson, JC. 2013. Analyzing Social Networks. Sage: London. A new UCINET-oriented book on SNA is coming out in late May, early June, 2013. Here's the entry in the Sage catalog. If you like, take a look at the Preface and the Introduction.

    • Borgatti, S.P. & Halgin, D.S. (2011). On Network Theory. Organization Science. September/October 2011 22(5):1168-1181 [pdf]

    • UCINET Quick-Start Guide [pdf]

    • Hanneman, Robert A. and Mark Riddle. 2005. Introduction to social network methods. Riverside, CA: University of California, Riverside [html]

Advanced SNA

    • Bonacich, P. 1987. "Power and Centrality: A Family of Measures."American Journal of Sociology92:1170-1182. [^pdf]

    • Borgatti, S.P. and Everett, M.G. 2006. A graph-theoretic perspective on centrality. [pdf].

    • Borgatti, S.P. 2005. Centrality and network flow. Social Networks. 27(1): 55-71. [pdf]

Stochastic Models

    • Robins, G., P. Pattison, Y. Kalish, and D. Lusher (2007). On exponential random graph models for cross-sectional analysis of complete networks: An introduction to exponential random graph (p*) models for social networks. Social Networks, 29(2): 173-191 [pdf]