The transformation of populist discourse in the Good Party: A comparison of the 2019 local elections and 2023 general elections based on Meral Akşener’s speeches
2026
84 pages
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Advisor: Doç. Dr. Recep GÜLMEZ
Abstract (EN)
This thesis compares the transformation of populist discourse in the İYİ Party through Meral Akşener’s speeches during the 2019 local and 2023 general election periods. Without classifying the party as populist or non-populist, it examines its frequency and contexts. The dataset comprises 16 parliamentary group and campaign rally speeches: seven from 2019 and nine from 2023. Using comparative discourse analysis and qualitative coding, sentences, paragraphs, and passages were examined in MAXQDA. Six codes were applied: people-centrism, anti-elitism, the us-them divide, moral dualism/Manichaean framing, crisis/threat/urgency, and exclusive representation/anti-pluralism. The analysis identified 918 coded segments, 471 in 2019 and 447 in 2023. Moral dualism and anti-elitism remained dominant; moral dualism occurred in 122 segments in each period. People-centrism declined from 102 to 75 and crisis/threat/urgency from 69 to 56, whereas exclusive representation/anti-pluralism increased from 41 to 62. The us-them divide was the least frequent code in both periods. These findings indicate continuity in moral opposition and elite criticism, alongside a stronger emphasis on representation and legitimacy in 2023. Frequencies were interpreted with selected passages and political contexts, rather than as self-sufficient findings. By examining an opposition party across two electoral settings, the thesis contributes to broader research on populist discourse in Turkey.
Institution

Erzincan Binali Yıldırım University
Division of Political Science and Public Administration
How to Cite
Ömer Temel (Master Thesis). The transformation of populist discourse in the Good Party: A comparison of the 2019 local elections and 2023 general elections based on Meral Akşener’s speeches, 2026, pp. 1-84, Erzincan Binali Yıldırım University, DOI: https://doi.org/10.71008/ebyu.thesis.2026.274.
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