Targeting Your Preferences: Modelling Micro-Targeting for an Increasingly Diverse Electorate
Toby Pilditch () and
Jens Koed Madsen ()
Journal of Artificial Societies and Social Simulation, 2021, vol. 24, issue 1, 5
The use of data to inform and run political campaigning has become an inescapable trend in recent years. In attempting to persuade an electorate, micro-targeted campaigns (MTCs) have been employed to great effect through the use of tailored messaging and selective targeting. Here we investigate the capacity of MTCs to deal with the diversity of political preferences across an electorate. More precisely, via an Agent-Based Model we simulate various diverse electorates that encompass single issue, multiple issue, swing, and disengaged voters (among others, including combinations thereof) and determine the relative persuasive efficacy of MTCs when pitted against more traditional, population-targeting campaigns. Taking into account the perceived credibility of these campaigns, we find MTCs highly capable of handling greater voter complexity than shown in previous work, and yielding further advantages beyond traditional campaigns in their capacity to avoid inefficient (or even backfiring) interactions â€“ even when fielding a low credibility candidate.
Keywords: Micro-Targeted Campaigning; Cognitive Modelling; Source Credibility; Political Messaging; Simulation; Bayesian Modelling (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:jas:jasssj:2020-73-2
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