Vera Sosnovik defended her PhD thesis entitled “Detection and analysis of online issue and political ads”.
Supervisors:
Mme. Oana Goga- CNRS
M. Patrick Loiseau – Inria
The thesis committee consists of:
Rapporteurs:
M. Kévin Huguenin – Université de Lausanne
M. Walter Rudametkin – University of Lille
Examiner:
M. Gilles Bastin – Sciences Po Grenoble
M. Paolo Frasca – CNRS
Mme. Juhi Kulshrestha – Aalto University
The defense took place at Auditorium IMAG (Grenoble) on the 4th of September at 14:00.
Abstract
Online political advertising has become the cornerstone of political campaigns. The budget spent solely on political advertising in the U.S. has increased by more than 100% from $700 million during the 2017-2018 U.S. election cycle to $1.6 billion during the 2020 U.S. presidential elections. Naturally, the capacity offered by online platforms to micro-target ads with political content has been worrying lawmakers, journalists, and online platforms, especially after the 2016 U.S. presidential election, where Cambridge Analytica has targeted voters with political ads congruent with their personality.
To curb such risks, both online platforms and regulators (through the DSA act proposed by the European Commission) have agreed that researchers, journalists, and civil society need to be able to scrutinize the political ads running on large online platforms. Consequently, online platforms such as Meta and Google have implemented Ad Libraries that contain information about all political ads running on their platforms.
The thesis consists of three contributions related to the online political advertising problems. The first project investigates whether we can reliably distinguish political ads from non-political ads. We take an empirical approach to analyze what kind of ads are deemed political by ordinary people and what kind of ads lead to disagreement. Our results show a significant disagreement between what ad platforms, ordinary people, and advertisers consider political and suggest that this disagreement mainly comes from diverging opinions on which ads address social issues. Overall our results imply that it is important to consider social issue ads as political, but they also complicate political advertising regulations.
In the second project, we focus on political ads that are related to policy. Understanding which policies politicians or organizations promote and to whom is essential in determining dishonest representations. We propose automated methods based on pre-trained models to classify ads in 14 main policy groups identified by the Comparative Agenda Project (CAP). We discuss several inherent challenges that arise. Finally, we analyze policy-related ads featured on Meta platforms during the 2022 French presidential elections period.
In the final contribution we propose a set of practical benchmarks to evaluate the “goodness” of political ad definitions. The benchmarks aim to assess whether the definitions can capture a set of truly problematic ads (the true positives), such as ads with divisive messages across demographic groups, and the ability to not capture a set of ads that only have humanitarian scopes (the false positives). We evaluate two definitions from online platforms and two definitions from policymakers based on our benchmarks. Our results show that definitions that only cover ads from/about political actors, and elections miss the highest percentage of advertisements that are divisive across different demographic groups.
