Quantifying Data-Driven Campaigning Across Sponsors and Platforms

Michael M. Franz, Meiqing Zhang, Travis N. Ridout, Pavel Oleinikov, Jielu Yao, Furkan Cakmak and Erika Franklin Fowler
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Michael M. Franz: Department of Government and Legal Studies, Bowdoin College, USA
Meiqing Zhang: Wesleyan Media Project, Wesleyan University, USA
Travis N. Ridout: School of Politics, Philosophy, and Public Affairs, Washington State University, USA
Pavel Oleinikov: Wesleyan Media Project, Wesleyan University, USA / Quantitative Analysis Center, Wesleyan University, USA
Jielu Yao: East Asian Institute, National University of Singapore, Singapore
Furkan Cakmak: Wesleyan Media Project, Wesleyan University, USA
Erika Franklin Fowler: Department of Government, Wesleyan University, USA

Media and Communication, 2024, vol. 12

Abstract: Although modern data-driven campaigning (DDC) is not entirely new, scholars have typically relied on reports and interviews of practitioners to understand its use. However, the advent of public ad libraries from Meta and Google provides an opportunity to measure the scope and variation in DDC practice in advertising across different types of sponsors and within sponsors across platforms. Using textual and audiovisual processing, we create a database of ads from the 2022 US elections. These data allow us to create an index that quantifies the extent of DDC at the level of the sponsor and platform. This index takes into account both the number of unique creatives placed and the similarity across those creatives. In addition, we explore the impact of sponsor resources, the office being sought, and the competitiveness of the race on the measure of DDC sophistication. Ultimately, our research establishes a measurement strategy for DDC that can be applied across ad sponsors, campaigns, parties, and even countries. Understanding the extent of DDC is vital for policy discussions surrounding the regulation of microtargeting and data privacy.

Keywords: data-driven campaigning; digital campaigning; election campaigns; political advertising (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:cog:meanco:v12:y:2024:a:8577

DOI: 10.17645/mac.8577

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