Most methods used to make theory-relevant observations of technology use rely on self-report or application logging data where individuals' digital experiences are purposively summarized into aggregates meant to describe how the average individual engages with broadly defined segments of content. This aggregation and averaging masks heterogeneity in how and when individuals actually engage with their technology. In this study, we use screenshots (N > 6 million) collected every 5five seconds that were sequenced and processed using text and image extraction tools into content-, context-, and temporally-informative “screenomes” from 132 smartphone users over several weeks to examine individuals' digital experiences. Analyses of screenomes highlight extreme between-person and within-person heterogeneity in how individuals switch among and titrate their engagement with different content. Our simple quantifications of textual and graphical content and flow throughout the day illustrate the value screenomes have for the study of individuals' smartphone use and the cognitive and psychological processes that drive use. We demonstrate how temporal, textual, graphical, and topical features of people's smartphone screens can lay the foundation for expanding the Human Screenome Project with full-scale mining that will inform researchers' knowledge of digital life.
All Science Journal Classification (ASJC) codes
- Arts and Humanities (miscellaneous)
- Human-Computer Interaction