Cover Image
QR Code

Beyond content: discriminatory power of function words in text type classification.

Our work aims to evaluate the strength of the association between function words and several text types: novels, poems, academic articles, reviews, and blog posts, and the accuracy of their classification to these categories, through machine-learning and statistical methods. The principal conclusion...

Full description

Published in:Digital Scholarship in the Humanities Vol. 39; no. 2; pp. 765 - 790
Main Authors: Venglařová, Klára, Matlach, Vladimír
Format: Article
Published: Oxford University Press / USA Jun2024
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=177947258&site=ehost-live
header:
  @attributes:
    shortDbName: hlh
    uiTerm: 177947258
    longDbName: Humanities International Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        2055768X
        JEO9
      jtl: Digital Scholarship in the Humanities
      issn: 2055768X
      maglogo: N
    pubinfo:
      dt: Jun2024
      vid: 39
      iid: 2
      pid: 622
      pub: Oxford University Press / USA
    artinfo:
      ui:
        177947258
        10.1093/llc/fqae013
      ppf: 765
      ppct: 25
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
              size: 3.3MB
      tig:
        atl: Beyond content: discriminatory power of function words in text type classification.
      aug:
        au:
          Venglařová, Klára
          Matlach, Vladimír
        affil: Department of General Linguistics, Palacký University , Olomouc, 779 00, Czech Republic
      su: Attribution of authorship
      sug:
        subj: Attribution of authorship
      keyword:
        authorship attribution
        function words
        support vector machine
        text type attribution
      ab: Our work aims to evaluate the strength of the association between function words and several text types: novels, poems, academic articles, reviews, and blog posts, and the accuracy of their classification to these categories, through machine-learning and statistical methods. The principal conclusion is that the types of texts are distinguishable based only on the function words, either by vocabulary or vocabulary diversity. Such findings may impact the techniques of authorship attribution based on function words and text clustering techniques since some function words add information about the text types/genres, in addition to content words.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: Y
      custom: © 2019 EADH: The European Association for Digital Humanities.
      item: Digital Scholarship in the Humanities
      holder: Oxford University Press / USA
      dt:
        @attributes:
          year: 2024
    holdings:
      @attributes:
        islocal: N