Aligning Emotions: A Comparative Analysis of Text and Imagery by European Party Leaders on Instagram

Abstract

This study explores the interplay of imagery and text in online political communication by European party leaders. We examine how visual and textual components combine to convey emotions in Instagram posts published by one hundred twenty-four mainstream and populist leaders of one hundred fourteen parties in twenty-four EU countries, covering 3 months before and after the 2019 European elections. Images are analyzed through automated face and emotion recognition algorithms to determine whether they contain positive, negative, or neutral emotions. The text accompanying each post is analyzed through a large language model algorithm. Results indicate that populist leaders, particularly right-wing ones, are less likely to combine positive textual and visual elements. Compared to mainstream leaders, right-wing populists more frequently post contents where text and image are redundantly nonpositive. Finally, emotional mismatch between textual and visual components is common among both mainstream and populist leaders.