Annotating and Identifying Emotions in Text Metadata

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Title

  • Main Title Annotating and Identifying Emotions in Text

Creator

  • Author: Strapparava, Carlo, 1962-
    Creator Type: Personal
    Creator Info: Human Language Technology Group; Fondazione Bruno Kessler
  • Author: Mihalcea, Rada, 1974-
    Creator Type: Personal
    Creator Info: University of North Texas

Publisher

  • Name: Springer-Verlag
    Place of Publication: [Berlin, Germany]

Date

  • Creation: 2010

Language

  • English

Description

  • Content Description: This book chapter discusses annotating and identifying emotions in text.
  • Physical Description: 18 p.

Subject

  • Keyword: lexical semantics
  • Keyword: emotion analysis

Source

  • Book: Intelligent Information Access, 2010. Berlin: Springer-Verlag, v. 301/2010, pp. 21-38.

Collection

  • Name: UNT Scholarly Works
    Code: UNTSW

Institution

  • Name: UNT College of Engineering
    Code: UNTCOE

Rights

  • Rights Access: public

Resource Type

  • Book Chapter

Format

  • Text

Identifier

  • DOI: 10.1007/978-3-642-14000-6_2
  • Archival Resource Key: ark:/67531/metadc31010

Degree

  • Academic Department: Computer Science and Engineering

Note

  • Display Note: Abstract: This paper focuses on the classification of emotions and polarity in news headlines and it is meant as an exploration of the connection between emotions and lexical semantics. The authors first describe the construction of the data set used in evaluation exercise "Affective Text" task at SemEval 2007, annotated for six basic emotions: Anger, Disgust, Fear, Joy, Sadness, and Surprise, and for Positive and Negative polarity. The authors also briefly describe the participating systems and their results. Second, exploiting the same data set, the authors propose and evaluate several knowledge-based and corpus-based methods for the automatic identification of emotions in text.