Methodology for network interference

Dec 14, 2018

I led a discussion on several intriguing papers on methods to address network interference in the seminar class provided by Prof. Sinan Aral. Topics include network exposure, graph cluster randomization, and bias reduction in networked experiments. I am happy to explore in this research area in the future. Please let me know if you have any thoughts to discuss with me!

I share my notes here.

References:

[1] Peter M. Aronow, and Cyrus Samii. "Estimating average causal effects under general interference, with application to a social network experiment." The Annals of Applied Statistics 11.4 (2017): 1912-1947.

[2] Johan Ugander, et al. "Graph cluster randomization: Network exposure to multiple universes." Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2013.

[3] Dean Eckles, Brian Karrer, and Johan Ugander. "Design and analysis of experiments in networks: Reducing bias from interference." Journal of Causal Inference 5.1 (2017).

[4] Sinan Aral. Networked experiments. Oxford, UK: Oxford University Press, 2016.

Last update: Dec 14, 2018