Record Details


Field	Value

Title	Replication Data for "Measuring and understanding parties' anti-elite strategies"

Identifier	https://doi.org/10.7910/DVN/T0UKCN

Creator	Licht, Hauke

Publisher	Harvard Dataverse

Description	This repository contains code and data to replicate the analysis in the JOP article "Measuring and understanding parties' anti-elite strategies" Paper Abstract: 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.

Subject	Social Sciences

Date	2024-02-26

Contributor	Licht, Hauke

ICAR Research Data Repository for Knowledge Management