  While many apps include built-in options to report bugs or request features,
users still provide an increasing amount of feedback via social media, like
Twitter. Compared to traditional issue trackers, the reporting process in
social media is unstructured and the feedback often lacks basic context
information, such as the app version or the device concerned when experiencing
the issue. To make this feedback actionable to developers, support teams engage
in recurring, effortful conversations with app users to clarify missing context
items. This paper introduces a simple approach that accurately extracts basic
context information from unstructured, informal user feedback on mobile apps,
including the platform, device, app version, and system version. Evaluated
against a truthset of 3014 tweets from official Twitter support accounts of the
3 popular apps Netflix, Snapchat, and Spotify, our approach achieved precisions
from 81% to 99% and recalls from 86% to 98% for the different context item
types. Combined with a chatbot that automatically requests missing context
items from reporting users, our approach aims at auto-populating issue trackers
with structured bug reports.
