RE-AIMing Predictive Text

Matthew Higgs, Claire McCallum, Selina Sutton, Mark Warner


Abstract
Our increasing reliance on mobile applications means much of our communication is mediated with the support of predictive text systems. How do these systems impact interpersonal communication and broader society? In what ways are predictive text systems harmful, to whom, and why? In this paper, we focus on predictive text systems on mobile devices and attempt to answer these questions. We introduce the concept of a ‘text entry intervention’ as a way to evaluate predictive text systems through an interventional lens, and consider the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) of predictive text systems. We finish with a discussion of opportunities for NLP.
Anthology ID:
2021.hcinlp-1.17
Volume:
Proceedings of the First Workshop on Bridging Human–Computer Interaction and Natural Language Processing
Month:
April
Year:
2021
Address:
Online
Venues:
EACL | HCINLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
109–115
Language:
URL:
https://aclanthology.org/2021.hcinlp-1.17
DOI:
Bibkey:
Cite (ACL):
Matthew Higgs, Claire McCallum, Selina Sutton, and Mark Warner. 2021. RE-AIMing Predictive Text. In Proceedings of the First Workshop on Bridging Human–Computer Interaction and Natural Language Processing, pages 109–115, Online. Association for Computational Linguistics.
Cite (Informal):
RE-AIMing Predictive Text (Higgs et al., HCINLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.hcinlp-1.17.pdf