• The Words Themselves: A Content-based Approach to Quote Attribution

    Author(s):
    Adam Hammond, Graeme Hirst, Krishnapriya Vishnubhotla (see profile)
    Date:
    2020
    Group(s):
    DH2020
    Subject(s):
    Literary style--Statistical methods
    Item Type:
    Video
    Tag(s):
    Stylometry
    Permanent URL:
    http://dx.doi.org/10.17613/sbfx-9b18
    Abstract:
    Quote attribution is the identification of the speaker of a quotation in a given text. It requires reasoning about conversational patterns and contextual clues, and is especially complex in literary texts. We present a semi-supervised iterative classification approach to quote attribution that is based on ideas from computational stylometry, using the content of the quotation to distinguish between speakers. We achieve an accuracy of 77.3% on the QuoteLi quote attribution corpus. Despite certain limitations, we show that our method is a competitive alternative to systems based on contextual clues, and a viable complement to them.
    Notes:
    Subtitle file available on the Dh2020 discussion post.
    Metadata:
    Status:
    Published
    Last Updated:
    2 years ago
    License:
    All Rights Reserved
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