Description
This research focuses on the relationship between the textual and emotional content of authoritarian populism and opinionated public sentiment taking the 2023 Turkish presidential election campaigns on Twitter as a case study. It will analyse the candidates' personality traits, discursive styles, emotional patterns of political messages, and public reaction to policy offerings. To learn more about the candidates' electoral and communicative strategies, supervised machine learning programs and emotion dictionaries namely LICW and Python will be used for data collection and analysis. Focusing on election campaign periods allows one to reveal the differences and similarities between President Tayyip Erdogan and opposition leader Kemal Kilicdaroglu. Displaying the political and sentimental spectrum at the societal and leadership level helps us hear the voice of the longest-surviving populist regime in history, and crack the codes of populist mobilisation by understanding the main motivations, aspirations, and triggering factors behind it from a multidimensional scope.
