Abstract
Populist party communication is a growing research area. However, measuring the concept empirically is challenging due to the context sensitivity of such rhetoric. In this paper, we present an approach that relies on a computer-assisted methods of text analysis to study populist communication on social media that accounts for this problem. We focus on party communication on Facebook in Germany over a period of three years. Based on this data, populist communication is identified using computer-assisted keyword detection, which is sensitive to wording change dynamics and varying word use across parties employing populist communication and reduces the amount of manual coding. A comparison of the approach using a pre-defined keyword list, a validity test with expert evaluations of the salience of anti-elite rhetoric and an application of the data are presented to explore how it relates to existing research and the opportunities it offers.
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