Observations on typing from 136 million keystrokes

Vivek Dhakal, Anna Maria Feit, Per Ola Kristensson, Antti Oulasvirta

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

25 Citations (Scopus)
65 Downloads (Pure)

Abstract

We report on typing behaviour and performance of 168,000 volunteers in an online study. The large dataset allows detailed statistical analyses of keystroking patterns, linking them to typing performance. Besides reporting distributions and confirming some earlier findings, we report two new findings. First, letter pairs typed by different hands or fingers are more predictive of typing speed than, for example, letter repetitions. Second, rollover-typing, wherein the next key is pressed before the previous one is released, is surprisingly prevalent. Notwithstanding considerable variation in typing patterns, unsupervised clustering using normalised inter-key intervals reveals that most users can be divided into eight groups of typists that differ in performance, accuracy, hand and finger usage, and rollover. The code and dataset are released for scientific use.

Original languageEnglish
Title of host publicationCHI '18 Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
PublisherACM
ISBN (Electronic) 978-1-4503-5620-6
DOIs
Publication statusPublished - 20 Apr 2018
MoE publication typeA4 Article in a conference publication
EventACM SIGCHI Annual Conference on Human Factors in Computing Systems - Palais des Congrès de Montréal, Montreal, Canada
Duration: 21 Apr 201826 Apr 2018
Conference number: 36
https://chi2018.acm.org/
https://chi2018.acm.org

Conference

ConferenceACM SIGCHI Annual Conference on Human Factors in Computing Systems
Abbreviated titleCHI
CountryCanada
CityMontreal
Period21/04/201826/04/2018
Internet address

Keywords

  • Large-scale study
  • Modern typing behavior
  • Text entry

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