The CAST-framework: Measure and model social media use as a multi-level phenomenon through real-world applications

2026-09-14

AI Summary

为理解社交媒体使用如何影响福祉，提出CAST框架，通过多维度测量和建模个体在不同时间尺度上的行为、生理及体验。

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.

Problem

• social media use
• well-being
• measurement
• content and context
• behavior and experience

Innovation

• CAST framework
• multi-level phenomenon
• synchronized measurement modules
• well-being