Predicting Authorship and Author Traits from Keystroke Dynamics

    Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

    Abstract

    Written text transmits a good deal of non-verbal information related to the author’s identity and social factors, such as age, gender and personality. However, it is less known to what extent behavioral biometric traces transmit such information. We use typist data to study the predictiveness of authorship, and present first experiments on predicting both age and gender from keystroke dynamics. Our results show that the model based on keystroke features leads to significantly higher accuracies for authorship than the text-based system, while being two orders of magnitude smaller. For user attribute prediction, the best approach is to combine the two, suggesting that extra- linguistic factors are disclosed to a larger degree in written text, while author identity is better transmitted in typing behavior.
    Original languageEnglish
    Title of host publicationProceedings of the 2nd Workshop on Computational Modeling of People's Opinions, Personality and Emotions in Social Media (PEOPLES 2018), NAACL workshop
    PublisherAssociation for Computational Linguistics
    Publication date2018
    Pages98-104
    ISBN (Electronic)978-1-948087-17-9
    DOIs
    Publication statusPublished - 2018
    EventThe 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Workshop on Computational Modeling of People's Opinions, Personality and Emotions in Social Media (PEOPLES) - New Orleans, New Orleans, United States
    Duration: 6 Jun 20186 Jun 2018

    Conference

    ConferenceThe 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
    LocationNew Orleans
    Country/TerritoryUnited States
    CityNew Orleans
    Period06/06/201806/06/2018

    Keywords

    • Keystroke Dynamics
    • Authorship Prediction
    • Behavioral Biometrics
    • Age and Gender Prediction
    • Typist Data Analysis

    Fingerprint

    Dive into the research topics of 'Predicting Authorship and Author Traits from Keystroke Dynamics'. Together they form a unique fingerprint.

    Cite this