<p>The use of social bots by cryptocurrency manipulators to affect the market price has recently emerged as a potential concern in the cryptocurrency market. This study investigates the contribution of social bots to sentiment diffusion on social media and explores the mechanisms underlying cryptocurrency manipulation. We applied 15 machine learning algorithms to examine LUNA price dynamics using 1032 price points and sentiments extracted from 33,281 tweets collected on Twitter (now X) between April 15 and May 27, 2022. The sentiment features consist of two sentiment polarities (positive and negative) and eight basic emotion categories (anger, anticipation, disgust, fear, joy, sadness, surprise, and trust). The results reveal that social bots were highly active during this period, and the sentiments they expressed were more predictive of LUNA prices than those of human accounts, highlighting their important role in the LUNA crash. This study also examines the affective mechanisms through which social bots assist manipulators in triggering herd behavior among investors and investigates the relationship between bot-generated sentiment and price dynamics. The interaction analysis reveals that mixed emotions serve as informative predictors of LUNA’s upward and downward price dynamics. Overall, this study highlights the role of social bots in driving sentiment and price fluctuations, illustrating their impact on cryptocurrency market stability and cyberspace governance.</p>