Machine Learning for Public Administration Research, with Application to Organizational Reputation

46 Pages Posted: 25 May 2018 Last revised: 13 Oct 2018

See all articles by Lefteris Jason Anastasopoulos

Lefteris Jason Anastasopoulos

University of Georgia - Department of Public Administration and Policy; University of Georgia - School of Public and International Affairs

Andrew B. Whitford

University of Georgia - Department of Public Administration and Policy

Date Written: May 14, 2018

Abstract

Machine learning methods have gained a great deal of popularity in recent years among public administration scholars and practitioners. These techniques open the door to the analysis of text, image and other types of data that allow us to test foundational theories of public administration and to develop new theories. Despite the excitement surrounding machine learning methods, clarity regarding their proper use and potential pitfalls is lacking. This paper attempts to fill this gap in the literature through providing a machine learning “guide to practice” for public administration scholars and practitioners. Here, we take a foundational view of machine learning and describe how these methods can enrich public administration research and practice through their ability develop new measures, tap into new sources of data and conduct statistical inference and causal inference in a principled manner. We then turn our attention to the pitfalls of using these methods such as unvalidated measures and lack of interpretability. Finally, we demonstrate how machine learning techniques can help us learn about organizational reputation in federal agencies through an illustrated example using tweets from 13 executive federal agencies. All R code, analyses and data described in this paper can be found in the Online Appendix.

Keywords: organizational reputation, machine learning, public administration, text analysis, gradient boosted trees

JEL Classification: H83, C55, D83

Suggested Citation

Anastasopoulos, Lefteris Jason and Whitford, Andrew B., Machine Learning for Public Administration Research, with Application to Organizational Reputation (May 14, 2018). Available at SSRN: https://ssrn.com/abstract=3178287 or http://dx.doi.org/10.2139/ssrn.3178287

Lefteris Jason Anastasopoulos (Contact Author)

University of Georgia - Department of Public Administration and Policy ( email )

Athens, GA 30602
United States

University of Georgia - School of Public and International Affairs ( email )

Athens, GA 30602-6254
United States

Andrew B. Whitford

University of Georgia - Department of Public Administration and Policy ( email )

Athens, GA 30602
United States
706-542-2898 (Phone)
706-583-0610 (Fax)

HOME PAGE: http://andrewwhitford.com

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