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The Old Boy (and Girl) Network: Social Network Formation on University Campuses


Adalbert Mayer


Texas A&M University - Department of Economics

Steven L. Puller


Texas A&M University

July, 27 2008

Journal of Public Economics, Vol. 92, pp. 329-347,2008

Abstract:     
This paper documents the structure and composition of social networks on university campuses and investigates the processes that lead to their formation. Using administrative data and information from Facebook.com, we document the factors that are the strongest predictors of whether two students are friends. Race is strongly related to social ties, even after controlling for a variety of measures of socioeconomic background, ability, and college activities. We develop a model of the formation of social networks that decomposes the formation of social links into effects based upon the exogenous school environment and effects of endogenous choice arising from preferences for certain characteristics in one's friends. We use student-level data from an actual social network to calibrate the model. We simulate the social network under alternative university policies aimed at reducing social segmentation. We find that changes in the school environment that affect the likelihood that two students interact have only a limited potential to reduce the racial segmentation of the social network.

Keywords: social networks, higher education, racial segregation

JEL Classification: I20, J15, J62, Z13

Accepted Paper Series


Date posted: July 30, 2008  

Suggested Citation

Mayer, Adalbert and Puller, Steven L., The Old Boy (and Girl) Network: Social Network Formation on University Campuses (July, 27 2008). Journal of Public Economics, Vol. 92, pp. 329-347,2008. Available at SSRN: http://ssrn.com/abstract=1180942

Contact Information

Adalbert Mayer
Texas A&M University (TAMU) - Department of Economics ( email )
5201 University Blvd.
College Station, TX 77843-4228
United States
Steven L. Puller (Contact Author)
Texas A&M University (TAMU) ( email )
Department of Statistics
College Station, TX 77843-4353
United States
Feedback to SSRN (Beta)


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