Universitat Ramon Llull. Esade
2025-01-12
Representing and interpreting human opinions within an unstructured framework is inherently complex. Hesitant fuzzy linguistic term sets offer a comprehensive context that facilitates a nuanced understanding of diverse perspectives. This study introduces a methodology that integrates sentiment analysis with hesitant fuzzy linguistic term sets to effectively aggregate and compare news from diverse sources. By employing linguistic scales, our approach enhances the interpretation of various perceptions and attitudes, facilitating comprehensive knowledge extraction and representation. The main objective of this research is to conduct a comparative analysis of news coverage across European countries in relation to the Israel–Gaza war. This analysis aims to capture the multifaceted sensitivities surrounding the ongoing situation, highlighting how different nations perceive the conflict.
Article
Published version
English
Linguistic modeling; Knowledge extraction; Knowledge representation; Unbalanced hesitant fuzzy linguistic term sets
13 p.
MDPI
Machine Learning and Knowledge Extraction, Vol. 7(1)
Esade [293]