Abstract
In an era in which media platforms such as TikTok, Instagram and YouTube increasingly privilege algorithmic optimisation of behaviour, the dominant audience metrics measure how long or how often users stay but rarely why they stay or what they take away. Furthermore, algorithmic systems are increasingly shaping what audiences see and thus how they engage, which raises questions about the epistemic and organisational role of metrics in meaning-making. This research proposes the concept of “metrics of meaning”, a multidimensional framework that complements traditional dashboards of audience behaviour with deeper indicators of relevance, trust, conversational quality, community value and impact. Drawing on literature in audience engagement and algorithmic mediation, the framework outlines three key dimensions: (1) Trust metrics — how audiences perceive credibility and authenticity of content providers; (2) Conversational depth — quality of audience interaction (not just volume of comments); (3) Attentional quality — cognitive engagement, full-view rates, and meaning-making rather than mere dwell. For example, while algorithmic logs may show that a video was watched to completion, qualitative follow-up can reveal whether the viewer found it meaningful or trustworthy, or whether it influenced their practice or discourse. By rethinking audience measurement through the lenses of culture, cognition and ethics, this paper invites media professionals and scholars to design smarter, multidimensional metrics that value not only performance but purpose. The goal is not to abandon measurement, but to redefine it: shifting from counting attention to understanding resonance.
Presenters
Samela LimaDean, School of Communication and Innovation, Adventist University of Sao Paulo, São Paulo, Brazil
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
KEYWORDS
Algorithmic engagement, Audience measurement, Datafication of communication, Cultural analytics
