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

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Palin, Kseniia
dc.contributor.author Feit, Anna Maria
dc.contributor.author Kim, Sunjun
dc.contributor.author Kristensson, Per Ola
dc.contributor.author Oulasvirta, Antti
dc.date.accessioned 2019-11-07T12:10:12Z
dc.date.available 2019-11-07T12:10:12Z
dc.date.issued 2019-10-01
dc.identifier.citation 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 . , a9 , ACM , International Conference on Human-Computer Interaction with Mobile Devices and Services , Taipei , Taiwan, Republic of China , 01/10/2019 . https://doi.org/10.1145/3338286.3340120 en
dc.identifier.isbn 9781450368254
dc.identifier.other PURE UUID: fb3c6bd4-7998-4ea6-a83f-792059aa19aa
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/how-do-people-type-on-mobile-devices-observations-from-a-study-with-37000-volunteers(fb3c6bd4-7998-4ea6-a83f-792059aa19aa).html
dc.identifier.other PURE LINK: http://www.scopus.com/inward/record.url?scp=85073536418&partnerID=8YFLogxK
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/38210172/ELEC_Palin_How_do_People_type_MobileHCI.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/41198
dc.description | openaire: EC/H2020/637991/EU//COMPUTED | openaire: EC/H2020/717054/EU//OPTINT
dc.description.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. en
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation info:eu-repo/grantAgreement/EC/H2020/717054/EU//OPTINT
dc.relation.ispartof International Conference on Human-Computer Interaction with Mobile Devices and Services en
dc.relation.ispartofseries Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019 en
dc.rights openAccess en
dc.subject.other Computer Networks and Communications en
dc.subject.other Information Systems en
dc.subject.other Human-Computer Interaction en
dc.subject.other Software en
dc.subject.other 113 Computer and information sciences en
dc.title How do people type on mobile devices? Observations from a study with 37,000 volunteers en
dc.type A4 Artikkeli konferenssijulkaisussa fi
dc.description.version Peer reviewed en
dc.contributor.department User Interfaces
dc.contributor.department Swiss Federal Institute of Technology Zurich
dc.contributor.department University of Cambridge
dc.contributor.department Helsinki Institute for Information Technology HIIT
dc.contributor.department Department of Communications and Networking en
dc.subject.keyword Computer Networks and Communications
dc.subject.keyword Information Systems
dc.subject.keyword Human-Computer Interaction
dc.subject.keyword Software
dc.subject.keyword 113 Computer and information sciences
dc.identifier.urn URN:NBN:fi:aalto-201911076203
dc.identifier.doi 10.1145/3338286.3340120
dc.type.version publishedVersion


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