The Promise and Perils of Using Big Data in the Study of Corporate Networks: Problems, Diagnostics and Fixes

Eelke Heemskerk, Kevin Young, Frank W. Takes, Bruce Cronin, Javier Garcia-Bernardo, Lasse F. Henriksen, William Kindred Winecoff, Vladimir Popov, Audrey Laurin-Lamothe

    Research output: Contribution to journalJournal articleResearchpeer-review


    Network data on connections between corporate actors and entities – for instance through co-ownership ties or elite social networks – are increasingly available to researchers interested in probing the many important questions related to the study of modern capitalism. Given the analytical challenges associated with the nature of the subject matter, variable data quality and other problems associated with currently available data on this scale, we discuss the promise and perils of using big corporate network data (BCND). We propose a standard procedure for helping researchers 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 through a specific work-flow procedure. For each step in this procedure, we provide a set of best practices for how to identify, resolve and minimize the BCND problems that arise.
    Original languageEnglish
    JournalGlobal Networks: A Journal of Transnational Affairs
    Issue number1
    Pages (from-to)3-32
    Number of pages30
    Publication statusPublished - Jan 2018

    Bibliographical note

    Published online: 4 December 2017


    • Big corporate network data
    • Big data
    • Corporate networks
    • Diagnostics
    • Network data quality

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