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Emotion models for textual emotion classification

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00305612" target="_blank" >RIV/68407700:21230/16:00305612 - isvavai.cz</a>

  • Result on the web

    <a href="http://iopscience.iop.org/article/10.1088/1742-6596/772/1/012063" target="_blank" >http://iopscience.iop.org/article/10.1088/1742-6596/772/1/012063</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1088/1742-6596/772/1/012063" target="_blank" >10.1088/1742-6596/772/1/012063</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Emotion models for textual emotion classification

  • Original language description

    This paper deals with textual emotion classification which gained attention in recent years. Emotion classification is used in user experience, product evaluation, national security, and tutoring applications. It attempts to detect the emotional content in the input text and based on different approaches establish what kind of emotional content is present, if any. Textual emotion classification is the most difficult to handle, since it relies mainly on linguistic resources and it introduces many challenges to assignment of text to emotion represented by a proper model. A crucial part of each emotion detector is emotion model. Focus of this paper is to introduce emotion models used for classification. Categorical and dimensional models of emotion are explained and some more advanced approaches are mentioned.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JC - Computer hardware and software

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2016

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Journal of Physics: Conference Series

  • ISBN

  • ISSN

    1742-6596

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

  • Publisher name

    Institute of Physics Publishing

  • Place of publication

    Bristol

  • Event location

    University of California, Berkeley

  • Event date

    Aug 3, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article