The CAST-framework: Measure and model social media use as a multi-level phenomenon through real-world applications
TL;DR
This work introduces the CAST framework to connect measurement choices with person-specific models of exposure, behavior, physiology, and experience and proposes four synchronized measurement modules linking mobile and wearable data with self-reports and intervention responses.
Abstract
Designing social media experiences that support well-being requires understanding when, how, and for whom use matters. Screen-time totals omit content and context, and connecting these with behavior and experience requires coordinating measurements across timescales. We introduce the CAST framework to connect measurement choices with person-specific models of exposure, behavior, physiology, and experience. Its dimensions specify where observations occur, how they are obtained, what they measure, and at what temporal resolution. Responses to interventions, such as whether to proceed after an app-opening pause, enter as behavioral measurements. We propose four synchronized measurement modules linking mobile and wearable data with self-reports and intervention responses. A synthetic demonstration with 120 simulated participants over 28 days illustrates how daily aggregation can obscure opposing effects of different activities under specified generating assumptions. The framework guides selection of measures and outcomes for evaluating social media interfaces and interventions.
