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.
|Title of host publication||Transformative Practice and Research in Organizational Communication|
|Number of pages||16|
|State||Published - Jul 12 2017|
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ASJC Scopus subject areas
- Economics, Econometrics and Finance (all)
- Business, Management and Accounting (all)