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  • Book
  • Jul 2024

Computational Methods for Affect Detection from Natural Language

Authors:

  1. Alexandra Balahur-Dobrescu

    1. European Commision Joint Research Centre, Ispra, Italy

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  2. Maite Taboada

    1. Department of Linguistics, Simon Fraser University, Burnaby, Canada

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    You can also search for this author in PubMed   Google Scholar

  3. Björn W. Schuller

    1. TU München LS für Mensch-Maschine-Kommunikation, München, Germany

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  • Offers a broad overview of natural language processing in affective computing
  • Familiarizes readers with current approaches in affective computing with explanations of theory as well as practical examples
  • Introduces and defines the concepts employed in the computational treatment of affect from text, from an inter-disciplinary, unified perspective
  • A timely topic for the age of social media

Part of the book series: Computational Social Sciences (CSS)

About this book

A broad overview of natural language processing in affective computing is given by this title. Its goal is to familiarize the reader with current approaches in affective computing as well as the most relevant concepts related to this field (affect, sentiment, subjectivity and others). Research in human affect has a long established tradition in social sciences - Philosophy, Psychology, Socio-psychology, Cognitive Science, Pragmatics, Marketing, Communication. The study of affect from a computational point of view is a recent field in Artificial Intelligence, denominated “Affective Computing”. Despite the novelty of the subject, the volume and importance of research in automatic human affect recognition, classification and simulation has been constantly growing in the past decades, leading to the development of further sub-areas of research. One of these directions deals with the study of automatic affect treatment from text, in the Artificial Intelligence area of Natural Language Processing. In this context, different tasks have been developed, from emotion detection, subjectivity analysis, opinion mining to sentiment analysis and appraisal analysis.
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Keywords

  • Affect in AI
  • Affective Computing
  • Emotion Detection
  • Multilingual Sentiment Analysis
  • Multilinguality
  • Opinion Mining
  • Opinion Trend Analysis
  • Sentiment Analysis
  • Social Media Analysis
  • Subjectivity Analysis
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Authors and Affiliations

  • European Commision Joint Research Centre, Ispra, Italy

    Alexandra Balahur-Dobrescu

  • Department of Linguistics, Simon Fraser University, Burnaby, Canada

    Maite Taboada

  • TU München LS für Mensch-Maschine-Kommunikation, München, Germany

    Björn W. Schuller

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Bibliographic Information

  • Book Title: Computational Methods for Affect Detection from Natural Language

  • Authors: Alexandra Balahur-Dobrescu, Maite Taboada, Björn W. Schuller

  • Series Title: Computational Social Sciences

  • Publisher: Springer Cham

  • eBook Packages: Education, Education (R0)

  • Copyright Information: Springer Nature Switzerland AG 2024

  • Hardcover ISBN: 978-3-319-00601-7Due: 11 August 2024

  • eBook ISBN: 978-3-319-00602-4Due: 11 August 2024

  • Series ISSN: 2509-9574

  • Series E-ISSN: 2509-9582

  • Edition Number: 1

  • Number of Pages: 250

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