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An Introduction to Computational Social Science for Organizational Communication

An Introduction to Computational Social Science for Organizational Communication

Andrew N. Pilny, Marshall Scott Poole
Copyright: © 2018 |Pages: 17
ISBN13: 9781522528234|ISBN10: 1522528237|EISBN13: 9781522528241
DOI: 10.4018/978-1-5225-2823-4.ch011
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MLA

Pilny, Andrew N., and Marshall Scott Poole. "An Introduction to Computational Social Science for Organizational Communication." Transformative Practice and Research in Organizational Communication, edited by Philip J. Salem and Erik Timmerman, IGI Global, 2018, pp. 184-200. https://doi.org/10.4018/978-1-5225-2823-4.ch011

APA

Pilny, A. N. & Poole, M. S. (2018). An Introduction to Computational Social Science for Organizational Communication. In P. Salem & E. Timmerman (Eds.), Transformative Practice and Research in Organizational Communication (pp. 184-200). IGI Global. https://doi.org/10.4018/978-1-5225-2823-4.ch011

Chicago

Pilny, Andrew N., and Marshall Scott Poole. "An Introduction to Computational Social Science for Organizational Communication." In Transformative Practice and Research in Organizational Communication, edited by Philip J. Salem and Erik Timmerman, 184-200. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-2823-4.ch011

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Abstract

The exponential growth of “Big Data” has given rise to a field known as computational social science (CSS). The authors view CSS as the interdisciplinary investigation of society that takes advantage of the massive amount of data generated by individuals in a way that allows for abductive research designs. Moreover, CSS complicates the relationship between data and theory by opening the door for a more data-driven approach to social science. This chapter will demonstrate the utility of a CSS approach using examples from dynamic interaction modeling, machine learning, and network analysis to investigate organizational communication (OC). The chapter concludes by suggesting that lessons learned from OC's history can help deal with addressing several current issues related to CSS, including an audit culture, data collection ethics, transparency, and Big Data hubris.

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