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Sources of variation in social networks

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  • Atalay, Enghin

Abstract

What explains the large variation in the number of contacts (degree) that different participants of social networks have: age, randomness, or some unobservable fitness measure? To answer this question, I extend the model presented in Jackson and Rogers (2007) to allow individuals to vary in their ability to attract contacts. I estimate the parameters of the extended model, using a social network of citations among high-energy physics papers, and find that the extended Jackson–Rogers model can parsimoniously fit the degree distribution of each age cohort. Moreover, both the length of time spent in the network and the unobservable fitness measure are important in explaining the observed variation in participantsʼ degrees.

Suggested Citation

  • Atalay, Enghin, 2013. "Sources of variation in social networks," Games and Economic Behavior, Elsevier, vol. 79(C), pages 106-131.
    • Handle: RePEc:eee:gamebe:v:79:y:2013:i:c:p:106-131
    DOI: 10.1016/j.geb.2013.01.009
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    References listed on IDEAS

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    1. Bramoullé, Yann & Currarini, Sergio & Jackson, Matthew O. & Pin, Paolo & Rogers, Brian W., 2012. "Homophily and long-run integration in social networks," Journal of Economic Theory, Elsevier, vol. 147(5), pages 1754-1786.
    2. Thomas Chaney, 2014. "The Network Structure of International Trade," American Economic Review, American Economic Association, vol. 104(11), pages 3600-3634, November.
    3. Bronwyn H. Hall & Adam B. Jaffe & Manuel Trajtenberg, 2001. "The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools," NBER Working Papers 8498, National Bureau of Economic Research, Inc.
    4. Jackson, Matthew O. & Wolinsky, Asher, 1996. "A Strategic Model of Social and Economic Networks," Journal of Economic Theory, Elsevier, vol. 71(1), pages 44-74, October.
    5. Timothy G. Conley & Christopher R. Udry, 2010. "Learning about a New Technology: Pineapple in Ghana," American Economic Review, American Economic Association, vol. 100(1), pages 35-69, March.
    6. Michael Ostrovsky, 2008. "Stability in Supply Chain Networks," American Economic Review, American Economic Association, vol. 98(3), pages 897-923, June.
    7. Matthew O. Jackson & Brian W. Rogers, 2007. "Meeting Strangers and Friends of Friends: How Random Are Social Networks?," American Economic Review, American Economic Association, vol. 97(3), pages 890-915, June.
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    Cited by:

    1. Thomas Chaney, 2014. "The Network Structure of International Trade," American Economic Review, American Economic Association, vol. 104(11), pages 3600-3634, November.
    2. repec:spo:wpmain:info:hdl:2441/7an8r1ubqs93caeqs80puld0tp is not listed on IDEAS
    3. Swapnil Dhamal & Y. Narahari, 2015. "Formation of Stable Strategic Networks with Desired Topologies," Studies in Microeconomics, , vol. 3(2), pages 158-213, December.
    4. Lafond, Francois, 2012. "Learning and the structure of citation networks," MERIT Working Papers 2012-071, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    5. repec:hal:spmain:info:hdl:2441/7an8r1ubqs93caeqs80puld0tp is not listed on IDEAS
    6. Ghiglino, Christian & Tabasso, Nicole, 2015. "The dynamics of innovations and citations," Economics Letters, Elsevier, vol. 131(C), pages 94-97.

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    More about this item

    Keywords

    Degree distribution; Heterogeneous fitness; Network formation; Social networks;
    All these keywords.

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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