How do people type on mobile devices? Observations from a study with 37,000 volunteers

Kseniia Palin; Anna Maria Feit; Sunjun Kim; Per Ola Kristensson; Antti Oulasvirta

doi:10.1145/3338286.3340120

How do people type on mobile devices? Observations from a study with 37,000 volunteers

Kseniia Palin, Anna Maria Feit, Sunjun Kim, Per Ola Kristensson, Antti Oulasvirta

Department of Electrical Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

129 Scopus citations

Abstract

This paper presents a large-scale dataset on mobile text entry collected via a web-based transcription task performed by 37,370 volunteers. The average typing speed was 36.2 WPM with 2.3% uncorrected errors. The scale of the data enables powerful statistical analyses on the correlation between typing performance and various factors, such as demographics, finger usage, and use of intelligent text entry techniques. We report effects of age and finger usage on performance that correspond to previous studies. We also find evidence of relationships between performance and use of intelligent text entry techniques: auto-correct usage correlates positively with entry rates, whereas word prediction usage has a negative correlation. To aid further work on modeling, machine learning and design improvements in mobile text entry, we make the code and dataset openly available.

Original language	English
Title of host publication	Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019
Publisher	Association for Computing Machinery, Inc
ISBN (Electronic)	9781450368254
DOIs	https://doi.org/10.1145/3338286.3340120
State	Published - 1 Oct 2019
Event	21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019 - Taipei, Taiwan, Province of China Duration: 1 Oct 2019 → 4 Oct 2019

Publication series

Name	Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019

Conference

Conference	21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019
Country/Territory	Taiwan, Province of China
City	Taipei
Period	1/10/19 → 4/10/19

Bibliographical note

Publisher Copyright:
© 2019 Association for Computing Machinery.

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10.1145/3338286.3340120

Cite this

Palin, K., Feit, A. M., Kim, S., Kristensson, P. O., & Oulasvirta, A. (2019). How do people type on mobile devices? Observations from a study with 37,000 volunteers. In Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019 Article a9 (Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019). Association for Computing Machinery, Inc. https://doi.org/10.1145/3338286.3340120

Palin, Kseniia ; Feit, Anna Maria ; Kim, Sunjun et al. / How do people type on mobile devices? Observations from a study with 37,000 volunteers. Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019. Association for Computing Machinery, Inc, 2019. (Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019).

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title = "How do people type on mobile devices? Observations from a study with 37,000 volunteers",

abstract = "This paper presents a large-scale dataset on mobile text entry collected via a web-based transcription task performed by 37,370 volunteers. The average typing speed was 36.2 WPM with 2.3\% uncorrected errors. The scale of the data enables powerful statistical analyses on the correlation between typing performance and various factors, such as demographics, finger usage, and use of intelligent text entry techniques. We report effects of age and finger usage on performance that correspond to previous studies. We also find evidence of relationships between performance and use of intelligent text entry techniques: auto-correct usage correlates positively with entry rates, whereas word prediction usage has a negative correlation. To aid further work on modeling, machine learning and design improvements in mobile text entry, we make the code and dataset openly available.",

author = "Kseniia Palin and Feit, \{Anna Maria\} and Sunjun Kim and Kristensson, \{Per Ola\} and Antti Oulasvirta",

note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019 ; Conference date: 01-10-2019 Through 04-10-2019",

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doi = "10.1145/3338286.3340120",

language = "English",

series = "Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019",

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Palin, K, Feit, AM, Kim, S, Kristensson, PO & Oulasvirta, A 2019, How do people type on mobile devices? Observations from a study with 37,000 volunteers. in Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019., a9, Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019, Association for Computing Machinery, Inc, 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019, Taipei, Taiwan, Province of China, 1/10/19. https://doi.org/10.1145/3338286.3340120

How do people type on mobile devices? Observations from a study with 37,000 volunteers. / Palin, Kseniia; Feit, Anna Maria; Kim, Sunjun et al.
Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019. Association for Computing Machinery, Inc, 2019. a9 (Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - This paper presents a large-scale dataset on mobile text entry collected via a web-based transcription task performed by 37,370 volunteers. The average typing speed was 36.2 WPM with 2.3% uncorrected errors. The scale of the data enables powerful statistical analyses on the correlation between typing performance and various factors, such as demographics, finger usage, and use of intelligent text entry techniques. We report effects of age and finger usage on performance that correspond to previous studies. We also find evidence of relationships between performance and use of intelligent text entry techniques: auto-correct usage correlates positively with entry rates, whereas word prediction usage has a negative correlation. To aid further work on modeling, machine learning and design improvements in mobile text entry, we make the code and dataset openly available.

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Palin K, Feit AM, Kim S, Kristensson PO, Oulasvirta A. How do people type on mobile devices? Observations from a study with 37,000 volunteers. In Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019. Association for Computing Machinery, Inc. 2019. a9. (Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019). doi: 10.1145/3338286.3340120

How do people type on mobile devices? Observations from a study with 37,000 volunteers

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