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This article presents a new measure and analysis of parties' anti-elite appeals. In order to measure parties' anti-elite appeals we apply crowd-sourced coding, supervised machine learning, and novel cross-lingual transfer learning techniques to parties' Twitter posts.Our dataset records quarterly estimates of parties' anti-elite strategies for 20 countries between 2008 and 2021. Based on these indicators, we analyze whether parties' anti-elite rhetoric reflects the potential costs and benefits of this electoral strategy.We find that mainstream parties use anti-elite rhetoric less frequently when they are more likely to be included in the next governing coalition. When challenger parties do well in the polls they become more anti-elitist. Our article not only contributes to the literature on democratic competition by introducing and applying a new measure of anti-elite strategies, but also outlines a novel, modular and scalable procedure to measure party appeals using social media posts.
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Licht et al. (2024) studied this question.
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