Political Advertising on Facebook During the 2022 Australian Federal Election: A Social Identity Perspective

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Authors: Stefano Civelli, Pietro Bernardelle, Frank Mols, Gianluca Demartini
Cited by: 0

Abstract

Political advertising on social media has become an important component of contemporary election campaigns, yet most research has focused on voluntary voting systems in which mobilizing supporters is a central goal. This study examines political advertising on Meta platforms (Facebook and Instagram) during the 2022 Australian federal election, a context shaped by compulsory voting and therefore distinctive campaign incentives. Using data from Meta’s Ad Library, we analyze temporal, demographic, geographic, and textual patterns in advertisements published by political actors during the campaign. The Australian Labor Party and the Liberal Coalition dominated the digital advertising landscape in both spending and impressions, while smaller parties and independents adopted more selective strategies. Ad delivery varied across demographic groups, with major parties, the Greens, and the United Australia Party showing different age and gender skews, though the clearest form of targeting was geographic. Across content, major parties emphasized party branding and criticism of opponents, whereas smaller parties more often relied on issue-based messaging. Interpreted through political psychology perspectives, and particularly Social Identity Theory, these patterns are consistent with different forms of identity appeal: major parties appear to reinforce established partisan identities, while smaller actors seek to connect with voters through issue-based identities to capture the support of disaffected voters who are obligated to participate.

Fields of Study & Subjects

Social Media and Politics Gender Feminism and Media Populism Right-Wing Movements

Publication details

Journal / source
Proceedings of the International AAAI Conference on Web and Social Media
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Volume
20
Issue
1
Pages
563–577
Publication date
25 May 2026
Language
EN