Identification of typing behaviors from large keystroke dataset
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Journal Title
Journal ISSN
Volume Title
Perustieteiden korkeakoulu |
Master's thesis
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Authors
Date
2017-10-04
Department
Major/Subject
Computer Science
Mcode
SCI3042
Degree programme
Master’s Programme in Computer, Communication and Information Sciences
Language
en
Pages
45 + 3
Series
Abstract
In this thesis work, keystroke-level typing data of over 168000 participants are analyzed to understand determinants of transcription typing behaviors. Keystroke patterns are analyzed in detail and linked to typing performance. Inter-Key Intervals of letter pairs and other statistical indicators of typing performance are calculated and their distributions and statistical relations are studied. These analyses show, among other findings, that Inter-Key Intervals in typing distant letter pairs in the keyboard are more predictive than other letter pairs, e.g. letter repetitions. Rollover typing, where the next key is pressed before the previous key is released, is prevalent widely, linked to faster typing with high correlation. Finally, medoids-based (PAM) unsupervised clustering of participants is performed to identify groups of typists with similar typing characteristics, and the findings from the clusters are interpreted in terms of performance, accuracy, hand movements and rollover behaviors.Description
Supervisor
Oulasvirta, AnttiThesis advisor
Feit, AnnaKeywords
transcription typing, data analysis, text entry, typing performance, keystroke analysis