No open-access location is known for this record yet.
No open-access location is known for this record yet.
This article analyses the divergent affective discourse strategies employed by Donald Trump and Kamala Harris during their 2024 US presidential campaign speeches. It explores how both candidates mobilise similar emotions – anger, fear/anxiety, pride, love, courage/fearlessness, confidence/determination and hope – but with different consistencies, targeting distinct threats and protectors of US political culture. The study draws on the theoretical framework of the sociology of emotions, employing the emotion narrative heuristic. This approach integrates critical discourse analysis and discourse analysis of emotions. The study focuses on the relationship between social objects to which emotions are discursively attached and analyses the emotional dynamics they generate. The findings indicate that Trump positions himself as a heroic saviour, one who is protecting the nation from threats such as migration and weak leadership. This narrative fosters anger and fear among the nation’s citizens towards outsiders, while instilling them with pride and hope in his leadership. In contrast, Harris focuses on justice, opportunity and collective progress. She portrays Trump as a threat to democracy, thereby evoking anger and galvanising support for democratic values. Both candidates employ the core grammar of US political culture, namely success/prosperity, US primacy and security/safety. However, a critical distinction emerges in their depiction of threats and heroes, and the influence on their understanding of institutions and procedures within liberal democracy. Trump’s myopic populist approach personalises leadership, while Harris’s universalist stance prioritises institutionalism. This study underscores the role of emotion narratives in shaping political culture, revealing how they influence voter mobilisation and the broader democratic process.
Loading…
Stored only when both papers are in the corpus — 3 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.