Reframing algorithmic public opinion: Affect, recursive dynamics, and vernacular practices

This commentary builds on Alessandro Gandini, Silvia Keeling, and Urbano Reviglio's concept of algorithmic public opinion by positioning it in dialogue with my decade-long research on social media algorithms and politics in Southeast Asia, notably the notion of algorithmic enclaves. I offer three key interventions. First, I foreground affective textures as central to algorithmic circulation, emphasising the centrality of affect in the algorithmic marketing culture . Second, I propose a recursive model of public opinion, where opinions are continually re-formed through iterative feedback loops, blurring linear distinctions between process and product and foregrounding the cyclical entanglement between direct and indirect gatekeeping . Third, I introduce the idea of vernacular visibility modulation , revealing how ordinary users, through culturally embedded and affectively attuned practices, shape what becomes visible in algorithmic environments, while not necessarily acting strategically. Together, these interventions extend the current framework by attending to affective texture, the recursive dynamics, and the ambient forms of agency. Reversing the gaze, the commentary argues that insights from the non-Western context may offer critical comprehension into how algorithmically mediated public opinion is formed, felt and contested globally.