Abstract

This chapter introduces the foundational concepts, theoretical underpinnings, and contextual relevance of Computational Infodemiology, an emerging interdisciplinary field concerned with the modelling, detection, and intervention of information disorder in digital ecosystems. Beginning with an exploration of the term infodemic, its origins, evolution, and contemporary manifestations, the chapter distinguishes between information voids, misinformation, and disinformation, showing how these phenomena interact under conditions of uncertainty, algorithmic amplification, and social stress. The discussion advances by outlining how algorithmic feedback loops reinforce engagement-driven content exposure, facilitating echo chambers and confirmation bias within fragmented digital publics. The chapter then anchors the epistemological and ethical rationale of Computational Infodemiology through three key theoretical pillars: systemic intervention theory, which provides a critical systems framework for contextual boundary analysis and stakeholder inclusion; social norm formation theory, which explains how collective beliefs emerge, stabilise, and become internalised in digital environments, and Martha Nussbaum’s spheres of influence, which situate belief dynamics within overlapping sociocultural, institutional, and digital domains of authority and trust. Together, these frameworks underscore the necessity of moving beyond isolated content moderation efforts toward ethically grounded, reflexive, and system-aware approaches to information integrity. The chapter concludes by positioning Computational Infodemiology as a vital response to the epistemic challenges of our time, one that demands not only computational tools, but also sociopolitical sensitivity, participatory design, and pluralistic engagement with diverse knowledge systems.