Party Cues Shape Political Text Coding — A Surprising New Study

immigration policy Methodology @PSR&M 1 R file 2 Stata files 3 datasets Dataverse

Coding political texts might reflect coders' prior beliefs about parties.

Coders & Methods

Ten coders evaluated 200 immigration-related statements from election manifestos. Party affiliations were randomly assigned, including a control group without cues.

Key Findings

Coders showed pro-immigration bias for Green Party texts • Anti-immigration leanings increased with populist radical right labels • No effects found for mainstream center-left or center-right parties

Why It Matters

These results suggest coders use party identity as a heuristic when faced with ambiguous policy statements, revealing an implicit layer to political text coding that goes beyond objective analysis.

Article card for article: The Impact of Party Cues on Manual Coding of Political Texts

The Impact of Party Cues on Manual Coding of Political Texts was authored by Laurenz Ennser-Jedenastik and Thomas M. Meyer. It was published by Cambridge in PSR&M in 2018.