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: Automatic detection of irony
    sub title: opinion mining in microblogs and social media
  name:
    name part: Karoui, Jihen
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Benamara, Farah
    role:
      role term: author.
  name:
    name part: Moriceau, Véronique
    role:
      role term: author.
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: enk
    date issued: 2019
    issuance: monographic
  language:
    language term: eng
  language:
    language term: fre
  physical description:
    form: remote
    extent: 1 online resource
  abstract: In recent years, there has been a proliferation of opinion-heavy texts on the Web: opinions of Internet users, comments on social networks, etc. Automating the synthesis of opinions has become crucial to gaining an overview on a given topic. Current automatic systems perform well on classifying the subjective or objective character of a document. However, classifications obtained from polarity analysis remain inconclusive, due to the algorithms' inability to understand the subtleties of human language. Automatic Detection of Irony presents, in three stages, a supervised learning approach to predicting whether a tweet is ironic or not. The book begins by analyzing some everyday examples of irony and presenting a reference corpus. It then develops an automatic irony detection model for French tweets that exploits semantic traits and extralinguistic context. Finally, it presents a study of portability in a multilingual framework (Italian, English, Arabic).
  table of contents: From Opinion Analysis to Figurative Language Treatment -- Toward Automatic Detection of Figurative Language -- A Multilevel Scheme for Irony Annotation in Social Network Content -- Three Models for Automatic Irony Detection -- Towards a Multilingual System for Automatic Irony Detection -- Conclusion -- Categories of Irony Studied in Linguistic Literature.
  note: Jihen Karoui, Farah Benamara, Véronique Moriceau.
  note: Includes bibliographical references and index.
  subject:
    topic: Natural language processing (Computer science)
  subject:
    topic: Data mining
  subject:
    topic: Natural Language Processing
  subject:
    topic: Data Mining
  classification: QA76.9.N38 K37 2019
  classification: 006.3/5
  related item:
    title info:
      title: Cognitive science series
  identifier: 9781119671183
  identifier: 1119671183
  identifier: 9781119671220
  identifier: 1119671221
  identifier: 9781119671152
  identifier: 1119671159
  identifier: 9781786303998
  identifier: 9781119671220 Wiley
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: NhCcYBP
    record creation date: 191017
    record change date: 20260214195952.2
    record identifier: in00004687111
    language of cataloging:
      language term: eng