Energized and emotional? How German and Italian Politicians emotionally narrate energy policy in the EU Elections 2024

Climate change, climate policy, and energy transitions tend to aggravate social inequalities and provoke strong emotional responses among the public (Im et al., 2024; Ojala et al., 2021). These emotional reactions are not merely individual psychological responses; they are also influenced by the way emotions are employed in policy discourse. When using policy narratives, policy actors resort to emotionally charged stories to influence public opinion and policy processes (Shanahan et al., 2018). Policy narratives are according to the Narrative Policy Framework (NPF) used at all stages of the policy process and feature at least one character (such as heroes, victims, villains) and a public policy referent (Jones et al., 2023). Despite the important role of emotion in policy communication and policy narratives, particularly in relation to climate policy (Neckel & Hasenfratz, 2021), emotion’s role in policy research is only beginning to be explored (Durnová, 2022; Fullerton et al., 2023; Pierce, 2021; Pierce et al., 2024; Yordy et al., 2024). This study focuses on the emotional dimensions of policy communication during the 2024 European elections, a critical moment for European climate and energy policy amidst the rise of far-right parties. Given the energy sector’s significant role in EU emissions and the necessity of “green energy” in sustainable infrastructure, this paper investigates which energy and transition issues were particularly salient during the 2024 EU election and how these issues were emotionally debated by policy actors in Germany and Italy. Germany and Italy, two of the EU’s largest emitters, face similar challenges regarding their sustainable energy transitions, yet approaching them with different policies. Using a dataset of N = 7,104 Instagram posts on policy communication before and during the 2024 EU election, this study employs a mixed-methods approach, integrating dictionary-based quantitative with qualitative content analysis. Custom dictionaries were created and validated on 500 posts (recall = 0.87; precision = 0.80), with intercoder reliability assessed on 150 posts (α = 0.88), to identify post related to climate change, climate policy and energy, thereby identifying the “policy reference”. This resulted in N = 468 posts for Germany N = 592 posts for Italy. We then qualitatively coded the narrative characters to identify all relevant policy narratives. To explore the emotional dimensions of identified policy narratives, we coded for emotion words using dictionaries inductively developed for the public policy context first by Yordy et al. (2024) and later further developed by Fullerton et al. (2023, 2024). As to our knowledge, emotion dictionaries have rarely been applied within the NPF, this study aims to test how well this method works for tracing discrete emotions in policy narratives. By qualitatively revising the dictionary-based findings on emotional expressions, integrating them with NPF elements and inductive coding, we aim to provide an enhanced understanding of the emotional dimensions of energy transition debates and policy conflicts in Europe.