The Editor vs. The Algorithm: Returns to Data and Externalities in Online News

37 Pages Posted: 14 Jan 2020

See all articles by Jörg Claussen

Jörg Claussen

Ludwig Maximilian University of Munich (LMU) - Faculty of Business Administration (Munich School of Management); Copenhagen Business School - Department of Innovation and Organizational Economics

Christian Peukert

University of Lausanne (HEC)

Ananya Sen

Carnegie Mellon University

Date Written: 2019

Abstract

We run a field experiment to quantify the economic returns to data and informational ex-ternalities associated with algorithmic recommendation relative to human curation in the context of online news. Our results show that personalized recommendation can outperform human curation in terms of user engagement, though this crucially depends on the amount of personal data. Limited individual data or breaking news leads the editor to outperform the algorithm. Additional data helps algorithmic performance but diminishing economic returns set in rapidly. Investigating informational externalities highlights that personalized recommendation reduces consumption diversity. Moreover, users associated with lower levels of digital literacy and more extreme political views engage more with algorithmic recommendations.

Keywords: field experiment, economics of AI, returns to data, filter bubbles

JEL Classification: L820, L510, J240

Suggested Citation

Claussen, Jörg and Peukert, Christian and Sen, Ananya, The Editor vs. The Algorithm: Returns to Data and Externalities in Online News (2019). CESifo Working Paper No. 8012, Available at SSRN: https://ssrn.com/abstract=3518959

Jörg Claussen (Contact Author)

Ludwig Maximilian University of Munich (LMU) - Faculty of Business Administration (Munich School of Management) ( email )

Kaulbachstr. 45
Munich, DE 80539
Germany

Copenhagen Business School - Department of Innovation and Organizational Economics ( email )

Kilevej 14A
Frederiksberg, 2000
Denmark

Christian Peukert

University of Lausanne (HEC) ( email )

Unil Dorigny, Batiment Internef
Lausanne, 1015
Switzerland

Ananya Sen

Carnegie Mellon University ( email )

Pittsburgh, PA 15213-3890
United States

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