Algorithmic Agitation and Affective Engineering: AI-Driven Emotion Recognition and Strategic Communication in Contemporary Social Movements

In the current context where the digital social movement increasingly influences the shape of political discourse, artificial intelligence demonstrates a dual effect by capturing and guiding collective emotions. This study explores the intersection of affective computing and strategic communication, revealing how AI reconstructs the emotional mobilization mechanism and ethical framework in protest activities. Based on an interdisciplinary theoretical perspective, we apply facial recognition models, transformative text classifiers, and multimodal fusion technologies to conduct sentiment mapping of protest content on social platforms. Experimental data show that the emotion recognition scheme integrating multiple modalities has the highest classification accuracy (F1= 0.89), which makes it possible to accurately anchor emotions. The communication strategy designed from emotional portraits such as anger and fear increased the interactive participation rate by up to 42%. However, technological empowerment comes with profound ethical risksemotional manipulation can undermine the authenticity of public discussions, and data collection also faces litigation for privacy violations. The research empirically reveals the reshaping effect of emotional intelligence tools on the shape of collective actions and proposes a framework for ethical application that considers both emotional resonance and social responsibility, delineating the limits of technological intervention in the public domain.