🚨 Publication alert: Android log data are increasingly used in research, so @dougaparry and I have developed the first step-by-step tutorial on how to actually extract behavioral metrics from them. Read it now in Computational Communication Research: https://t.co/mtImrRaxN8
This paper is supposed to help researchers handle raw Android log data in a systematic manner and facilitate access to this rich source of information 🔑. Feel free to use and share it. Feedback is very welcome!
🚨 Publication alert: Android log data are increasingly used in research, so @dougaparry and I have developed the first step-by-step tutorial on how to actually extract behavioral metrics from them. Read it now in Computational Communication Research: https://t.co/mtImrRaxN8
The supp. material includes a working rendition in R code, an example data set with raw Android log data, and the data set that results from applying the code to it. There are also lists that helps identify background processes and app names 📋 - with a script to retrieve them.
Check out this blog post on a preprint article providing a tutorial for extracting use metrics from raw Android log data, created by @dougaparry and myself: https://t.co/N6AMF53rgv
It is worth a read for anyone working with such data 👩🏾💻!
🚨 New preprint! @dougaparry, @mjemmer, and I investigated the times, gratifications, locations, and activities alongside smartphone and app use in Germany 📱. To do so, we used a combination of surveys, MESM, logging, and data donations.
https://t.co/xhpSgZlZIF
I'm European.
I recently visited the USA for the first time since 2018, hitting up Las Vegas and New York City.
What I witnessed left me stunned.
15 American oddities I still can't wrap my head around:
🚨 New preprint! Android log data are increasingly used in research, but the process of extracting behavioral metrics from them is usually trivialized - so @dougaparry and I have developed the first step-by-step tutorial on how to do that.
https://t.co/phpAQnnlDZ