1 research outputs found
On Detecting Policy-Related Political Ads: An Exploratory Analysis of Meta Ads in 2022 French Election
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. This is the first step on a long path. Due to the
volume of available data, it is impossible to go through these ads manually,
and we now need automated methods and tools to assist in the scrutiny of
political ads.
In this paper, 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. This paper proposes
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.Comment: Proceedings of the ACM Web Conference 2023 (WWW '23), May 1--5, 2023,
Austin, TX, US