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Computational Methods for Affect Detection from Natural Language 1st ed. 2024 [Kõva köide]

  • Formaat: Hardback, 250 pages, kõrgus x laius: 235x155 mm, 250 p., 1 Hardback
  • Sari: Computational Social Sciences
  • Ilmumisaeg: 11-Aug-2024
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319006010
  • ISBN-13: 9783319006017
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  • Formaat: Hardback, 250 pages, kõrgus x laius: 235x155 mm, 250 p., 1 Hardback
  • Sari: Computational Social Sciences
  • Ilmumisaeg: 11-Aug-2024
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319006010
  • ISBN-13: 9783319006017
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.

This book offers a broad overview of natural language processing in affective computing. It presents a theoretical and practical overview of key research topics dealing with the computational treatment of affect from text.
Affect Computation from Text Main Concepts and Tasks.- Subjectivity
Analysis in Natural Language.- Sentiment Analysis.- Emotion Detection from
Text.- Dealing with Multilinguality in Affect Computation from Text.-
Applications of Affect Computation Opinion Trend and Social Media
Analysis.- Current Challenges and Envisaged Developments in Affect
Computation from Text.