Articles producció científica> Enginyeria Informàtica i Matemàtiques

Introducing sentiment analysis of textual reviews in a multi-criteria decision aid system

  • Datos identificativos

    Identificador: imarina:9139039
    Autores:
    Jabreel, MohammedMaaroof, NajlaaValls, AidaMoreno, Antonio
    Resumen:
    © 2020 by the authors. Licensee MDPI, Basel, Switzerland. Nowadays, most decision processes rely not only on the preferences of the decision maker but also on the public opinions about the possible alternatives. The user preferences have been heavily taken into account in the multi-criteria decision making field. On the other hand, sentiment analysis is the field of natural language processing devoted to the development of systems that are capable of analysing reviews to obtain their polarity. However, there have not been many works up to now that integrate the results of this process with the analysis of the alternatives in a decision support system. SentiRank is a novel system that takes into account both the preferences of the decision maker and the public online reviews about the alternatives to be ranked. A new mechanism to integrate both aspects into the ranking process is proposed in this paper. The sentiments of the reviews with respect to different aspects are added to the decision support system as a set of additional criteria, and the ELECTRE methodology is used to rank the alternatives. The system has been implemented and tested with a restaurant data set. The experimental results confirm the appeal of adding the sentiment information from the reviews to the ranking process.
  • Otros:

    Autor según el artículo: Jabreel, Mohammed; Maaroof, Najlaa; Valls, Aida; Moreno, Antonio
    Departamento: Enginyeria Informàtica i Matemàtiques
    e-ISSN: 2076-3417
    Autor/es de la URV: Al-Ziyadi, Najlaa Maaroof Wahib / Moreno Ribas, Antonio / Valls Mateu, Aïda
    Palabras clave: Sentiment analysis Opinion mining Multiple criteria decision aid Aspect-based sentiment analysis
    Resumen: © 2020 by the authors. Licensee MDPI, Basel, Switzerland. Nowadays, most decision processes rely not only on the preferences of the decision maker but also on the public opinions about the possible alternatives. The user preferences have been heavily taken into account in the multi-criteria decision making field. On the other hand, sentiment analysis is the field of natural language processing devoted to the development of systems that are capable of analysing reviews to obtain their polarity. However, there have not been many works up to now that integrate the results of this process with the analysis of the alternatives in a decision support system. SentiRank is a novel system that takes into account both the preferences of the decision maker and the public online reviews about the alternatives to be ranked. A new mechanism to integrate both aspects into the ranking process is proposed in this paper. The sentiments of the reviews with respect to different aspects are added to the decision support system as a set of additional criteria, and the ELECTRE methodology is used to rank the alternatives. The system has been implemented and tested with a restaurant data set. The experimental results confirm the appeal of adding the sentiment information from the reviews to the ranking process.
    Áreas temáticas: Química Process chemistry and technology Physics, applied Materials science, multidisciplinary Materials science (miscellaneous) Materials science (all) Materiais Instrumentation General materials science General engineering Fluid flow and transfer processes Engineering, multidisciplinary Engineering (miscellaneous) Engineering (all) Engenharias ii Engenharias i Computer science applications Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências agrárias i Ciência de alimentos Chemistry, multidisciplinary Biodiversidade Astronomia / física
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: naglaa592011@gmail.com antonio.moreno@urv.cat aida.valls@urv.cat
    Identificador del autor: 0000-0003-0614-5385 0000-0003-3945-2314 0000-0003-3616-7809
    Fecha de alta del registro: 2024-10-12
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://www.mdpi.com/2076-3417/11/1/216
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Applied Sciences-Basel. 11 (1): 1-26
    Referencia de l'ítem segons les normes APA: Jabreel, Mohammed; Maaroof, Najlaa; Valls, Aida; Moreno, Antonio (2021). Introducing sentiment analysis of textual reviews in a multi-criteria decision aid system. Applied Sciences-Basel, 11(1), 1-26. DOI: 10.3390/app11010216
    DOI del artículo: 10.3390/app11010216
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2021
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Chemistry, Multidisciplinary,Computer Science Applications,Engineering (Miscellaneous),Engineering, Multidisciplinary,Fluid Flow and Transfer Processes,Instrumentation,Materials Science (Miscellaneous),Materials Science, Multidisciplinary,Physics, Applied,Process Chemistry and Technology
    Sentiment analysis
    Opinion mining
    Multiple criteria decision aid
    Aspect-based sentiment analysis
    Química
    Process chemistry and technology
    Physics, applied
    Materials science, multidisciplinary
    Materials science (miscellaneous)
    Materials science (all)
    Materiais
    Instrumentation
    General materials science
    General engineering
    Fluid flow and transfer processes
    Engineering, multidisciplinary
    Engineering (miscellaneous)
    Engineering (all)
    Engenharias ii
    Engenharias i
    Computer science applications
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências agrárias i
    Ciência de alimentos
    Chemistry, multidisciplinary
    Biodiversidade
    Astronomia / física
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