Abstract
Analytic models segment the electorate into distinct categories. Comparatively, dynamic models allow for interaction between system components, as they unfold over time. As systems become increasingly complex, analytic models are increasingly unable to track the consequences of intervening into the system. Given the fact that elections are highly complex systems, they should not be managed using analytical and isolated models. This chapter discusses the management of elections as complex systems, and the use of numerical models to parameterise citizens, test interventions, and optimise strategy. According to journalistic and academic reports, micro-targeted campaigns tend to be analytic. As such, this chapter presents a possible future direction for the use of data in micro-targeted campaign management.
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Notes
- 1.
Recall A/B-testing is when campaigns test different versions of the same message for representative samples of the target audience before launching it publicly. When they know which message type is most effective, they can use it on the target audience in general. This helps refine, rest, and optimise persuasion and influence efforts.
- 2.
As with analytic micro-targeted campaigns, voter models can be as complicated as desired/possible. If it can be expressed computationally, it can be integrated within the dynamic model.
- 3.
Not to mention the introduction of the increasingly sensationalist 24-hour news cycles.
- 4.
For example, during the Boston Marathon bombing of 2013, users on Twitter identified a wrong suspect and shared his image despite the fact that the FBI stated the person was not a suspect.
- 5.
- 6.
Voter interaction also means that segmentation is no longer isolated bins, but parameters that may vary between voters.
- 7.
For good descriptions of building dynamic and complex models, see Miller and Page (2007).
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Madsen, J.K. (2019). From Analytic to Dynamic Micro-targeted Campaign Models. In: The Psychology of Micro-Targeted Election Campaigns. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-22145-4_11
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