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Autor(en): 
  • Björn W. Schuller
  • Maite Taboada
  • Alexandra Balahur-Dobrescu
  • Computational Methods for Affect Detection from Natural Language 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Vorankündigung
    Veröffentlichung:  ANGEKÜNDIGT (August 2024)  
    Genre:  Sprache 
     
    Application software / Applications of Graph Theory and Complex Networks / Artificial Intelligence / B / Communications engineering / telecommunications / Communications Engineering, Networks / Complex analysis, complex variables / Computational Linguistics / Computer and Information Systems Applications / Computer Appl. in Social and Behavioral Sciences / Computer applications in the social & behavioural sciences / Education / Electrical Engineering / Graph Theory / Mathematical physics / Natural language & machine translation / Natural language processing (Computer science) / Natural Language Processing (NLP) / Physics
    ISBN:  9783319006017 
    EAN-Code: 
    9783319006017 
    Verlag:  Springer Nature EN 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Computational Social Sciences  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  0 gr 
    Seiten:  250 
    Bewertung: Keine Bewertung vor Veröffentlichung möglich.
    Inhalt:
    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. The aim of the present book is to give a theoretical and practical overview of the most important topics of researchdealing with the computational treatment of affect from text. Its goal is to present the reader with the most relevant concepts related to this field (affect, sentiment, subjectivity and others), the existing research areas and familiarize them with the present approaches, with theoretical explanations and practical examples.
      



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