@misc{10481/106311,
year = {2025},
month = {8},
url = {https://hdl.handle.net/10481/106311},
abstract = {The use of informal language on social media and the sheer volume of information make it
difficult for a computer system to analyse it automatically. The aim of this work is to design
a new group decision-making method that applies two new consensus methods based
on sentiment analysis. This method is designed for application in the analysis of texts on
social media. To test the method, we will use posts from the so called social network X.
The proposed model differs from previous work in this field by defining a new degree
of subjectivity and a new degree of reliability associated with user opinions. This work
also presents two new consensus measures, one focused on measuring the number of
words classified as positive and negative and the other on analysing the percentage of
occurrence of those words. Our method allows us to automatically extract preferences from
the transcription of the texts used in the debate, avoiding the need for users to explicitly
indicate their preferences. The application to a real case of public investment demonstrates
the effectiveness of the approach in collaborative contexts that used natural language.},
organization = {MICIU/AEI/10.13039/501100011033 - ERDF/EU (PID2022-139297OB-I00)},
organization = {Regional Ministry of University, Research and Innovation -
European Union - Andalusia ERDF Programme 2021–2027 (project C-ING-165-
UGR23)},
publisher = {MDPI},
keywords = {Consensus},
keywords = {Group decision-making},
keywords = {Natural language processing},
title = {Consensus-Based Automatic Group Decision-Making Method with Reliability and Subjectivity Measures Based on Sentiment Analysis},
doi = {10.3390/a18080477},
author = {Bajaña-Zajía, Johnny and Trillo Vílchez, José Ramón and Cabrerizo Lorite, Francisco Javier and Morente-Molinera, Juan Antonio},
}