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Using Big Data and Algorithms to Determine the Effect of Geographically Targeted Advertising on Vote Intention: Evidence From the 2012 U.S. Presidential Election
Authors:Tobias Konitzer  David Rothschild  Shawndra Hill  Kenneth C. Wilbur
Affiliation:1. tobiask@stanford.edu
Abstract:We develop a new conceptualization of political advertising effects by looking at the effect of the marginal advertising dollar during the heat of presidential campaigns. We argue that in contrast to other studies investigating effects of political ads, our approach is more apt to capture the natural environment in which political ads are encountered during a presidential campaign. We focus on the intense inundation of political ads voters are confronted with in swing states in the weeks leading up to the presidential election, and argue that it is unclear a priori whether we should expect advertising to affect vote intention in that critical circumstance. We empirically validate this hypothesis using a trove of data from the 2012 campaign: daily polling in media markets around the country, detailed data on all registered voters in the country, all TV advertisements by market and exact airtime, and the entire Twitter corpus. We find that neither overall increases in advertising spending nor partisan imbalances in spending expanded the candidates’ electorate. In fact, total Designated Market Area (DMA)-level spending significantly moderates a negative relationship between spending advantages and advantages in vote intention, suggesting a boomerang effect of additional spending late in the campaign. In closing, we discuss the ramifications of our findings for future research, and stress the importance of research tracking advertising effects.
Keywords:Political Advertising Effects  Big Data  MRP
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