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Political Advertising Online and Offline

Sat, August 31, 2:00 to 3:30pm, Hilton, Columbia 12


A wealth of scholarship over the past two decades has analyzed the strategic use of political advertising in campaigns (Freedman and Goldstein 1999; Goldstein and Freedman 2002, 2000; Sides and Vavreck 2013; Franz and Ridout 2007; Franz et al. 2008; Krasno and Green 2008; Kahn and Kenney 1999; Fowler, Franz, and Ridout 2016). However, the vast majority of the insights provided in this literature rely almost exclusively on television despite the rapid growth in online advertising broadly and social media advertising. We know that technological developments have increasingly enabled more fine-grained targeting of voters even on television (Ridout et al. 2012; Lovett and Peress 2015), however, most of the concerns from scholars regarding accountability have to do with campaigns making different promises to different citizens online and offline. Therefore, the release of the social media archives in summer 2018 represent an enormous opportunity to examine and test theories of targeting across modes of communication to better understand the extent of targeting online and its relationship to traditional television advertising.

Drawing on data from the newly released social media archives and television data from the Wesleyan Media Project, we analyze and compare the strategic use and content of advertising on television to the online environment for all federal, gubernatorial and state legislative candidates in the 2018 election.

Given the lower cost barrier to advertising online, we generally expect candidates down ballot, challengers, and candidates in districts with lower DMA congruence to their districts to make wider use of online advertising. In addition, due to the narrowcasting of the online environment, we further expect more divisive issue content and more negativity among ads that intend to persuade online than on television.

Preliminary findings suggest more similarity across on and offline advertisements than might be expected.