42 Pages Posted: 4 Oct 2016 Last revised: 2 Feb 2017
Date Written: January 2017
Network data on connections among corporate actors and entities – for instance through co-ownership ties or elite social networks – is increasingly available to researchers interested in probing many important questions related to the study of modern capitalism. We discuss the promise and perils of using Big Corporate Network Data (BCND) given the analytical challenges associated with the nature of the subject matter, variable data quality, and other problems associated with currently available data at this scale. We propose a standard process for how researchers can deal with BCND problems. While acknowledging that different research questions require different approaches to data quality, we offer a schematic platform that researchers can follow to make informed and intelligent decisions about BCND issues and address these issues through a specific work-flow procedure. Within each step in this procedure, we provide a set of best practices for how to identify, resolve, and minimize BCND problems that arise.
Keywords: Corporate Networks, Big Data, Network Analysis, Data Quality, Diagnostics, Big Corporate Network Data
Suggested Citation: Suggested Citation
Heemskerk, Eelke M. and Young, Kevin and Takes, Frank and Cronin, Bruce and Garcia-Bernardo, Javier and Popov, Vladimir and Winecoff, W. Kindred and Henriksen, Lasse Folke and Laurin-Lamothe, Audrey, The Promise and Perils of Using Big Data in the Study of Corporate Networks: Problems, Diagnostics and Fixes (January 2017). Available at SSRN: https://ssrn.com/abstract=2846761 or http://dx.doi.org/10.2139/ssrn.2846761