Tradeoffs in Automated Political Advertising Regulation: Evidence from the COVID-19 Pandemic

20 Pages Posted: 20 May 2020 Last revised: 31 Dec 2020

See all articles by Grazia Cecere

Grazia Cecere

Institut Mines Telecom, Business School, LITEM

Clara Jean

Epitech & Université Paris Saclay

Vincent Lefrere

Institut Mines-Télécom Business School

Catherine E. Tucker

Massachusetts Institute of Technology (MIT) - Management Science (MS)

Date Written: December 30, 2020

Abstract

Digital platforms have experienced pressure to restrict and regulate political ad content as a matter of national urgency. Digital ad venues therefore need to identify ads as having political content in order to police whether or not they have appropriate disclosures. However, an algorithmic approach to the categorization may hit difficulties in times of rapid change and if there is not a consensus on what a political ad actually is. We collect data on European and American ads published in the Facebook Ad Library and show that algorithmic determination of what constitutes an issue of national importance resulted in COVID-19-related ads to be disqualified because they do not have an appropriate disclaimer. Our results show that ads run by governmental organizations to inform the population about COVID-19 are more likely to be banned by Facebook's algorithm than ads run by non-governmental organizations. We suggest that this implies that governmental organizations failed to recognize that COVID-19 was a matter of national significance and that ads referring to COVID-19 required a disclaimer. We show that this primarily affects European governmental organizations' ads. It seems that Facebook's policy related to "{Social Issues, Elections or Politics}'' ads is based on US political broadcasting and political advertising rules which are less familiar to European organizations. Our results suggest that in general, most parties, falling within the political ad space have difficulty determining what might be governed by political ad policy, especially in the context of national emergencies.

Keywords: Algorithmic Decision-Making, Ad Bans, Political Ads, COVID-19

JEL Classification: M3, K2

Suggested Citation

Cecere, Grazia and Jean, Clara and Lefrere, Vincent and Tucker, Catherine E., Tradeoffs in Automated Political Advertising Regulation: Evidence from the COVID-19 Pandemic (December 30, 2020). Available at SSRN: https://ssrn.com/abstract=3603341 or http://dx.doi.org/10.2139/ssrn.3603341

Grazia Cecere

Institut Mines Telecom, Business School, LITEM ( email )

9, rue Charles Fourier
Évry, Ile de France 91011
France

Clara Jean (Contact Author)

Epitech & Université Paris Saclay ( email )

24 rue pasteur
Le Kremlin-Bicêtre, 94270
France

Vincent Lefrere

Institut Mines-Télécom Business School ( email )

9 rue Charles Fourier
Evry, 91011
France

Catherine E. Tucker

Massachusetts Institute of Technology (MIT) - Management Science (MS) ( email )

100 Main St
E62-536
Cambridge, MA 02142
United States

HOME PAGE: http://cetucker.scripts.mit.edu

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