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    Computational Estimation of Personal Properties From Language

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    Alsadhan, Nasser
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    Abstract
    Research in natural language and other modalities is starting to shed light on individuals

    personal properties. Estimating the personal properties of an individual or a group of individuals

    is the task of detecting different behavioural signals and studying how they correlate

    with personal properties such as mental health, personality, and emotions.

    Multiple disciplines such as philosophy, psychology, sociology, and cognitive science

    focus on defining and detecting personal properties. With the ease of data collection and

    analysis, studying and analyzing personal properties has become an easier task. Computer

    science can contribute to this on-going research by building computational models that

    mimic or predict an individual/group’s personal properties.

    This kind of research is done through studying two different behavioural signals. In my

    research I focus on verbal signals by studying how language usage correlates with personal

    properties. The other behavioural signal is non-verbal, such as body language, number of

    friends, eating habits, etc.

    The contribution of my thesis can be broken down to two parts: building tools to estimate

    a set of individual/group’s personal properties from mainly online posts through their

    language usage, and comparing the effectiveness of different data analytic tools/representations

    in the space of personal properties.
    URI for this record
    http://hdl.handle.net/1974/26682
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    • School of Computing Graduate Theses
    • Queen's Graduate Theses and Dissertations
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