rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Learn about term frequency-inverse document frequency in text analysis in R with data from How ISIS uses Twitter dataset (2016)
  name:
    name part: Shi, Feng
    name part: active 2019
    role:
      role term: creator
    role:
      role term: author.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: enk
    date issued: 2019
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource : illustrations
  abstract: This dataset is designed for teaching the TFIDF in text analysis. The dataset is a subset of data derived from the 2016 How ISIS Uses Twitter dataset, and the example demonstrates how TFIDF scores reveal words that are representative of a document and distinguish the document from others. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for R.
  target audience: specialized
  note: Feng Shi.
  note: Includes bibliographical references and index.
  subject:
    title info:
      title: Twitter
  subject:
    name:
      name part: IS (Organization)
  subject:
    name:
      name part: IS (Organization)
  subject:
    title info:
      title: Twitter
  subject:
    topic: Discourse analysis
    topic: Study and teaching
  subject:
    topic: R (Computer program language)
  subject:
    topic: R (Langage de programmation)
  subject:
    topic: Discourse analysis
    topic: Study and teaching
  subject:
    topic: R (Computer program language)
  classification: P302 .S55 2019
  classification: 401.41
  identifier: 9781526489012
  identifier: 1526489015
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: SGPBL
    record creation date: 190116
    record change date: 20240923170207.0
    record identifier: in00005493255
    language of cataloging:
      language term: eng