Tag: Thomas Robinson

Beyond apps: a method to model full distributions of screen content over time to study media effects

We introduce smartphone screen content patterns (content patterns) as a new construct and propose an analytical framework that represents smartphone use as distributions of experienced screen content rather than summaries of time spent on devices or in apps. We operationalize content patterns using deep learning embeddings of moment-by-moment screenshots and formalize use periods as probability distributions over embedding space...

Risk Communication in Real Time: Examining Individuals’ Smartphone Use During the 2021 Texas Winter Disaster With Mobile Sensing

In this study, we provide a detailed description of how individuals encounter risk communication during extreme weather events by analyzing comprehensive records of all the content that 11 adults viewed on their smartphones (n = 162,418 screenshots collected via mobile sensing) over 5 days of the winter disaster that struck Texas in February 2021. Participants viewed substantial amounts of risk communication, which comprised, on average, 21% of their total smartphone use during the winter disaster...