Strategic Emotional Rhetoric in Political Social Media: A Comprehensive Analysis of Donald Trump’s Tweeting Patterns and Propagandistic Techniques in the Digital Age

Abstract

This study employs Python-based analysis to investigate how Donald Trump strategically leveraged propagandistic techniques and emotional rhetoric on Twitter (2009–2019) to shape public perception and advance his political agenda. Analyzing 43,913 original tweets through sentiment analysis, linguistic patterns, and temporal dynamics, we reveal Trump’s systematic use of name-calling (“fake”, “illegal”), glittering generalities (“greatness”), and plain folks appeals to cultivate a combative, relatable persona. Quantitative results show his preference for emotional punctuation (exclamation marks: 12,458), negative vocabulary (529 pejorative terms), and algorithm-optimized timing (e.g., breakfast hours) to amplify engagement. Temporal tweet patterns correlate with political milestones like his 2016 victory, illustrating digital rhetoric’s weaponization to bypass media gatekeepers. Applying promotional arts theory, we expose how emotional manipulation, algorithms, and propagandistic framing interact in political communication. Findings highlight Twitter as a battleground for symbolic reality, where simplified language, repetition, and adversarial narratives fuel polarization and in-group loyalty. This research advances political communication scholarship by elucidating how digital platforms enable leaders to exploit cognitive biases, emotional contagion, and algorithmic mechanics to redefine democratic discourse in the post-truth era.