Identifying writing tasks using sequences of keystrokes

Rianne Conijn, Menno van Zaanen

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

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    Abstract

    The sequences of keystrokes that are generated when writing texts contain information about the writer as well as the writing task and cognitive aspects of the writing process. Much research has been conducted in the area of writer identification. However, research on the analysis of writing processes based on sequences of keystrokes has received only a limited amount of attention. Therefore, in this study we try to identify properties of keystrokes that indicate cognitive load of the writing process. Moreover, we investigate the influence of these properties on the classification of texts written during two different writing tasks: copying a text and freeform generation of text. We show that we can identify properties that allow for the correct classification of writing tasks, which at the same time do not describe writer-specific characteristics. However, some properties are the result of an interaction between the typing characteristics of the writer and the writing task.
    Original languageEnglish
    Title of host publicationBenelearn 2017: Proceedings of the Twenty-Sixth Benelux Conference on Machine Learning
    Pages28-35
    Number of pages7
    Publication statusPublished - 2017
    EventAnnual Belgian-Dutch Conference on Machine Learning (BENELEARN 2017) - Eindhoven, Netherlands
    Duration: 9 Jun 201710 Jun 2017

    Conference

    ConferenceAnnual Belgian-Dutch Conference on Machine Learning (BENELEARN 2017)
    Abbreviated titleBenelearn 2017
    Country/TerritoryNetherlands
    CityEindhoven
    Period9/06/1710/06/17

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    • Distinguished Paper Award

      Conijn, M. A. (Recipient) & van Zaanen, M. (Recipient), 9 Jun 2017

      Prize

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