Advertisement

Estimating Peer-Influence Effects Under Homophily: Randomized Treatments and Insights

  • Niloy Biswas
  • Edoardo M. Airoldi
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

When doing causal inference on networks, there is interference among the units. In a social network setting, such interference among individuals is known as peer-influence. Estimating the causal effect of peer-influence under the presence of homophily presents various challenges. In this paper, we present results quantifying the error incurred from ignoring homophily when estimating peer-influence on networks. We then present randomized treatment strategies on networks which can help disentangle homophily from the estimation of peer-influence.

Keywords

Causal inference Statistical network analysis Social networks Interference Randomized experiment Peer-influence Homophily 

Supplementary material

References

  1. 1.
    E.M. Airoldi, D.M. Blei, S.E. Fienberg, E.P. Xing, Mixed membership stochastic block- models. J. Mach. Learn. Res. (2008)Google Scholar
  2. 2.
    J.D. Angrist, The perils of peer effects. Labour Econ. (2014)Google Scholar
  3. 3.
    S.Aral, D. Walker, Creating social contagion through viral product design: a randomized trial of peer influence in networks. Manag. Sci. (2011)Google Scholar
  4. 4.
    S. Athey, D. Eckles, G.W. Imbens, Exact P-values for network interference. J. Am. Stat. Assoc. (2016)Google Scholar
  5. 5.
    E. Bakshy, D. Eckles, R. Yan, I. Rosenn, Social influence in social advertising: Evidence from field experiments, in Proceedings of the 13th ACM Conference on Electronic Commerce, 2012Google Scholar
  6. 6.
    R.M. Bond, C.J. Fariss, J.J. Jones, A.D.I. Kramer, C. Marlow, J.E. Settle, J.H. Fowler, A 61-million-person experiment in social influence and political mobilization. Nature (2012)Google Scholar
  7. 7.
    P. Holland, K. Laskey, S. Leinhardt, Stochastic block models: first steps. Soc. Netw. (1983)Google Scholar
  8. 8.
    C.F. Manski, Identification of endogenous social effects: the reflection problem. Rev. Econ. Stud. (1993)Google Scholar
  9. 9.
    C.R. Shalizi, A.C. Thomas, Homophily and contagion are generically confounded in observational social network studies. Sociol. Methods Res. (2011)Google Scholar
  10. 10.
    P. Toulis, E. Kao, Estimation of causal peer influence effects. J. Mach. Learn. Res. (2013)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Department of StatisticsHarvard UniversityCambridgeUSA

Personalised recommendations