Contextualizing Smartphone-Typed Language With User Input Intention

Title data

Bemmann, Florian ; Koch, Timo K. ; Bergmann, Maximilian ; Stachl, Clemens ; Buschek, Daniel ; Schoedel, Ramona ; Mayer, Sven:
Contextualizing Smartphone-Typed Language With User Input Intention.
In: Proceedings of the Mensch Und Computer 2025. - New York, NY, USA : Association for Computing Machinery , 2025 . - pp. 520-526
ISBN 979-8-4007-1582-2
DOI: https://doi.org/10.1145/3743049.3748537

Official URL:

Abstract in another language

While the study of smartphone-typed language offers valuable insights for HCI and interdisciplinary research, existing data collection methods often fall short in providing context. Contextualizing text contents solely by the input target app does not allow for selecting them by the actual input intention of the user (e.g., sending a direct message, publishing a post). We present a method to study smartphone-typed language in the wild, which extracts the user’s input intention from a text field’s prompt text. Our approach enables distinguishing language contents by their channel (i.e., comments, messaging, search inputs), which allows filtering and pre-selecting text contents by the user’s input intention and type of language. We provide software libraries and the underlying categorization schema of our method. Researchers can apply this on-device in studies relying on smartphone-typed language. We outline which further opportunities for adaptation our general procedure motivates, to facilitate interdisciplinary studies in the wild.

Further data

Item Type:	Article in a book
Refereed:	Yes
Institutions of the University:	Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IX > Chair Applied Computer Science - Univ.-Prof. Dr. Daniel Buschek
Result of work at the UBT:	Yes
DDC Subjects:	000 Computer Science, information, general works > 004 Computer science
Date Deposited:	19 Feb 2026 07:44
Last Modified:	19 Feb 2026 07:44
URI:	https://eref.uni-bayreuth.de/id/eprint/96277