Investigating the Tradeoffs of Everyday Text-Entry Collection Methods

André Rodrigues; Hugo Nicolau; André R.B. Santos; Diogo Branco; Jay Rainey; David  Verweij; Jan David Smeddinck; Kyle Montague; Tiago Guerreiro

doi:10.1145/3491102.3501908

Investigating the Tradeoffs of Everyday Text-Entry Collection Methods

André Rodrigues^*, Hugo Nicolau, André R.B. Santos, Diogo Branco, Jay Rainey, David Verweij, Jan David Smeddinck, Kyle Montague, Tiago Guerreiro

^*Corresponding author for this work

Computer and Information Sciences Department

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

6 Citations (Scopus)

Abstract

Typing on mobile devices is a common and complex task. The act of typing itself thereby encodes rich information, such as the typing method, the context it is performed in, and individual traits of the person typing. Researchers are increasingly using a selection or combination of experience sampling and passive sensing methods in real-world settings to examine typing behaviours. However, there is limited understanding of the effects these methods have on measures of input speed, typing behaviours, compliance, perceived trust and privacy. In this paper, we investigate the tradeoffs of everyday data collection methods. We contribute empirical results from a four-week field study (N=26). Here, participants contributed by transcribing, composing, passively having sentences analyzed and reflecting on their contributions. We present a tradeoff analysis of these data collection methods, discuss their impact on text-entry applications, and contribute a flexible research platform for in the wild text-entry studies.

Original language	English
Title of host publication	CHI '22
Subtitle of host publication	CHI Conference on Human Factors in Computing Systems
Editors	Simone Barbosa, Cliff Lampe, Caroline Appert, David A. Shamma, Steven Drucker, Julie Williamson, Koji Yatani
Place of Publication	New York, US
Publisher	ACM
Pages	1-15
Number of pages	15
ISBN (Print)	9781450391573
DOIs	https://doi.org/10.1145/3491102.3501908
Publication status	Published - 29 Apr 2022
Event	ACM CHI 2022 - 900 Convention Center Blvd, New Orleans, LA, United States Duration: 30 Apr 2022 → 5 May 2022 https://chi2022.acm.org/

Conference

Conference	ACM CHI 2022
Country/Territory	United States
City	New Orleans, LA
Period	30/04/22 → 5/05/22
Internet address	https://chi2022.acm.org/

Keywords

Text entry
in-the-wild
touch behaviours
user experience
performance
data collection

Access to Document

10.1145/3491102.3501908

Cite this

Rodrigues, A., Nicolau, H., Santos, A. R. B., Branco, D., Rainey, J., Verweij, D., Smeddinck, J. D., Montague, K., & Guerreiro, T. (2022). Investigating the Tradeoffs of Everyday Text-Entry Collection Methods. In S. Barbosa, C. Lampe, C. Appert, D. A. Shamma, S. Drucker, J. Williamson, & K. Yatani (Eds.), CHI '22: CHI Conference on Human Factors in Computing Systems (pp. 1-15). Article 378 ACM. https://doi.org/10.1145/3491102.3501908

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title = "Investigating the Tradeoffs of Everyday Text-Entry Collection Methods",

abstract = "Typing on mobile devices is a common and complex task. The act of typing itself thereby encodes rich information, such as the typing method, the context it is performed in, and individual traits of the person typing. Researchers are increasingly using a selection or combination of experience sampling and passive sensing methods in real-world settings to examine typing behaviours. However, there is limited understanding of the effects these methods have on measures of input speed, typing behaviours, compliance, perceived trust and privacy. In this paper, we investigate the tradeoffs of everyday data collection methods. We contribute empirical results from a four-week field study (N=26). Here, participants contributed by transcribing, composing, passively having sentences analyzed and reflecting on their contributions. We present a tradeoff analysis of these data collection methods, discuss their impact on text-entry applications, and contribute a flexible research platform for in the wild text-entry studies.",

keywords = "Text entry, in-the-wild, touch behaviours, user experience, performance, data collection",

author = "Andr{\'e} Rodrigues and Hugo Nicolau and Santos, {Andr{\'e} R.B.} and Diogo Branco and Jay Rainey and David Verweij and Smeddinck, {Jan David} and Kyle Montague and Tiago Guerreiro",

note = "Funding Information: This project was partially supported by FCT through LASIGE Research Unit funding, ref. UIDB/00408/2020, LARSyS Research Unit funding, ref. UIDB/50009/2020, project mIDR (AAC 02/SAICT/-2017, project 30347, cofunded by COMPETE/FEDER/FNR), and the IDEA-FAST project which has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 853981. This Joint Undertaking receives support from the European Union{\textquoteright}s Horizon 2020 research and innovation programme and EFPIA and associated partners.; ACM CHI 2022 ; Conference date: 30-04-2022 Through 05-05-2022",

year = "2022",

month = apr,

day = "29",

doi = "10.1145/3491102.3501908",

language = "English",

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editor = "Simone Barbosa and Cliff Lampe and Caroline Appert and Shamma, {David A.} and Steven Drucker and Julie Williamson and Koji Yatani",

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Rodrigues, A, Nicolau, H, Santos, ARB, Branco, D, Rainey, J, Verweij, D, Smeddinck, JD, Montague, K & Guerreiro, T 2022, Investigating the Tradeoffs of Everyday Text-Entry Collection Methods. in S Barbosa, C Lampe, C Appert, DA Shamma, S Drucker, J Williamson & K Yatani (eds), CHI '22: CHI Conference on Human Factors in Computing Systems., 378, ACM, New York, US, pp. 1-15, ACM CHI 2022, New Orleans, LA, United States, 30/04/22. https://doi.org/10.1145/3491102.3501908

Investigating the Tradeoffs of Everyday Text-Entry Collection Methods. / Rodrigues, André; Nicolau, Hugo; Santos, André R.B. et al.
CHI '22: CHI Conference on Human Factors in Computing Systems. ed. / Simone Barbosa; Cliff Lampe; Caroline Appert; David A. Shamma; Steven Drucker; Julie Williamson; Koji Yatani. New York, US: ACM, 2022. p. 1-15 378.

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

TY - CHAP

T1 - Investigating the Tradeoffs of Everyday Text-Entry Collection Methods

AU - Rodrigues, André

AU - Nicolau, Hugo

AU - Santos, André R.B.

AU - Branco, Diogo

AU - Rainey, Jay

AU - Verweij, David

AU - Smeddinck, Jan David

AU - Montague, Kyle

AU - Guerreiro, Tiago

N1 - Funding Information: This project was partially supported by FCT through LASIGE Research Unit funding, ref. UIDB/00408/2020, LARSyS Research Unit funding, ref. UIDB/50009/2020, project mIDR (AAC 02/SAICT/-2017, project 30347, cofunded by COMPETE/FEDER/FNR), and the IDEA-FAST project which has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 853981. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA and associated partners.

PY - 2022/4/29

Y1 - 2022/4/29

N2 - Typing on mobile devices is a common and complex task. The act of typing itself thereby encodes rich information, such as the typing method, the context it is performed in, and individual traits of the person typing. Researchers are increasingly using a selection or combination of experience sampling and passive sensing methods in real-world settings to examine typing behaviours. However, there is limited understanding of the effects these methods have on measures of input speed, typing behaviours, compliance, perceived trust and privacy. In this paper, we investigate the tradeoffs of everyday data collection methods. We contribute empirical results from a four-week field study (N=26). Here, participants contributed by transcribing, composing, passively having sentences analyzed and reflecting on their contributions. We present a tradeoff analysis of these data collection methods, discuss their impact on text-entry applications, and contribute a flexible research platform for in the wild text-entry studies.

AB - Typing on mobile devices is a common and complex task. The act of typing itself thereby encodes rich information, such as the typing method, the context it is performed in, and individual traits of the person typing. Researchers are increasingly using a selection or combination of experience sampling and passive sensing methods in real-world settings to examine typing behaviours. However, there is limited understanding of the effects these methods have on measures of input speed, typing behaviours, compliance, perceived trust and privacy. In this paper, we investigate the tradeoffs of everyday data collection methods. We contribute empirical results from a four-week field study (N=26). Here, participants contributed by transcribing, composing, passively having sentences analyzed and reflecting on their contributions. We present a tradeoff analysis of these data collection methods, discuss their impact on text-entry applications, and contribute a flexible research platform for in the wild text-entry studies.

KW - Text entry

KW - in-the-wild

KW - touch behaviours

KW - user experience

KW - performance

KW - data collection

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U2 - 10.1145/3491102.3501908

DO - 10.1145/3491102.3501908

M3 - Chapter

SN - 9781450391573

SP - 1

EP - 15

BT - CHI '22

A2 - Barbosa, Simone

A2 - Lampe, Cliff

A2 - Appert, Caroline

A2 - Shamma, David A.

A2 - Drucker, Steven

A2 - Williamson, Julie

A2 - Yatani, Koji

PB - ACM

CY - New York, US

T2 - ACM CHI 2022

Y2 - 30 April 2022 through 5 May 2022

ER -

Investigating the Tradeoffs of Everyday Text-Entry Collection Methods

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Best Paper Award - Investigating the Tradeoffs of Everyday Text-Entry Collection Methods

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Investigating the Tradeoffs of Everyday Text-Entry Collection Methods

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Best Paper Award - Investigating the Tradeoffs of Everyday Text-Entry Collection Methods

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