Author: Diana Ignatovich

With smartphones now more prevalent in everyday life than ever before, understanding their use and its implications becomes increasingly necessary. While self-reporting in surveys is the method typically used to assess smartphone use, it is affected by various problems such as distorted retrospection, social desirability bias, and high aggregation. More advanced methods include the Experience Sampling Method (ESM), which presents multiple short surveys per day to limit the degree of retrospection, and logging (Android only), which accesses an internal log on the device itself that documents each user activity in extremely high resolution. Although the latter is the most precise and objective method available for assessing smartphone use, the raw data received from the log file requires extensive transformation to extract actual human behavior rather than technical artifacts. Still, this transformation was never documented systematically and researchers working with this input implemented arbitrary steps to extract the data they required. 

The preprint article Extracting Meaningful Measures of Smartphone Usage from Android Event Log Data: A Methodological Primer, authored by former Methods Lab fellow Douglas Parry and Methods Lab member Roland Toth, aims to provide a detailed step-by-step guide to extracting different levels of smartphone use from Android log data. Specifically, the guide helps identify glances (short checks without unlocking the device), sessions (uses from unlocking to locking), and episodes (single app uses) from such log files, allowing for further investigation. All steps are presented as pseudo-code as well as described in text. In addition, the Online Supplementary Material (OSM) contains the full pseudo-code, a rendition in the R programming language, a sample data set containing raw log data, and more helpful material.

This guide ultimately enhances our understanding of how humans interact with these versatile devices, particularly beneficial for projects within the social sciences and neighboring disciplines. While survey methods are recognized for their economical advantages and ease of administration, access to objective high-resolution data contributes a more refined perspective. We hope this article helps researchers identify valuable measures from raw android event log data, thereby making this rich data source more accessible and manageable than it has previously been.