From Affect to Action, Street to Screen: The Emotional Cycle of Feminist Resistance in Iran

This project investigates how affect circulates between street and digital spheres within the Women, Life, Freedom movement in Iran. It draws on Sara Ahmed’s cultural politics of emotion, Bennett and Segerberg’s connective action, Gerbaudo’s choreographed protest, Bayramoğlu’s countervisuality, and M. Al Malous’s work on mediatized embodiment. These frameworks allow affect to be treated not as a private psychological state but as a mobile, relational force produced and re-articulated across bodies, images, texts, and platforms. The central argument is that feminist contention operates through a bidirectional circulation: affect generated in the street becomes digitally reconfigured, and digital affect returns to material practice—what I conceptualize as Street → Platform → Street. The cycle begins with embodied street events—chants, gestures, micro-performances, and visual exposures—that produce intense affective energies such as grief, anger, solidarity, and courage. Because physical presence carries high material and security costs, much of this energy moves into digital media, where posts, stories, reels, poems, sound clips, and hashtags transform raw affect into a circulating emotional feed. Users remix this feed into personal narratives, memes, affective reposting, and aesthetic motifs that form affective publics. These mediated affective forms then return to the street: new slogans, bodily performances, placards, sonic repertoires, and protest aesthetics draw directly from digital templates, completing the loop and sustaining mobilization. To trace this loop empirically, the study integrates two analytic strands. The first is a linguistic–semantic layer using affect lexicons and supervised machine-learning classifiers applied to captions, hashtags, and narrative text. This layer identifies semantic clusters, affective intensity, and valence, while temporal alignment methods (cross-correlation and event-based windows) reveal whether digital posts follow, amplify, or anticipate street events, making directional affect-transfer visible. The second strand is a visual–auditory layer combining computer-vision motif detection with manual close reading. Frame-by-frame analysis identifies body framing, gesture repertoires, visual motifs, montage strategies, and sonic cues. Tracing repost and remix pathways shows how specific visual or sonic elements travel across platform networks and then reappear in on-the-ground performances. Sampling is stratified and hashtag-based to capture variation across time and stylistic registers. Each post, story, reel, or protest clip is treated as a unit of affective circulation. Network analysis of reposting, mentions, and hashtag co-occurrence reconstructs circulation chains; qualitative sequence analysis links these chains to observed street practices. Algorithmic curation is modeled as an intervening variable, with repost frequency, recurrence patterns, and reach metrics serving as proxies for amplification or suppression. The project also examines state attempts to disrupt the affective loop through street repression (arrests, dispersal) and digital repression (filtering, shadow-banning, takedowns, algorithmic suppression, and internet shutdowns). Documenting these tactics clarifies how affective–political ecosystems are produced, constrained, and strategically punctured. Ethical protocols include anonymizing vulnerable users, secure data storage, and reflexive consent procedures for re-using user-generated content where feasible. By combining computational, visual, and narrative methods, the study offers a multimodal, evidence-based account of how affective dynamics animate and sustain feminist resistance in Iran.