Guest Editors
Dr. Jesus Serrano-Guerrero, University of Castilla-La Mancha, Spain
Dr. Francisco P. Romero, University of Castilla-La Mancha, Spain
Dr. Antonio Gabriel Lopez-Herrera, University of Granada, Spain
Dr. Mohammad Bani-Doumi, Applied Science Private University, Jordan
Dr. Bashar Alshouha, Applied Science Private University, Jordan
Dr. Jose A. Olivas, University of Castilla-La Mancha, Spain
Summary
The meteoric proliferation of opinions on the Internet has led to need of analysis and processing techniques to truly comprehend the subjective perceptions of users. Opinion Mining and Affective Computing have emerged as two areas able to deal with the discovery of sentiments, beliefs, attitudes and emotions, which are the key to many new systems such as customized recommendation systems, mental health prevention systems, marketing analysis dashboards, disinformation detection, etc.
The motivation of this Special Issue stems from the inherent challenges in creating technologies, techniques, and resources on Opinion Mining and Affective Computing based on the most recent technologies on Artificial Intelligence and Natural Language Processing such as Deep Learning, Large Language Models, or Explainability. The topics covered by this Special Issue are (but not limited):
· Disinformation, misinformation, malinformation
· Explainable sentiment and emotion analysis
· Large language models for sentiment and emotion detection
· Deep Learning architectures for sentiment and emotion classification
· Aspect-based Opinion Mining
· Multi-modal opinion analysis
· Hatred detection
· Resources Opinion Mining and Affective Computing
· Applications on Opinion Mining and Affective Computing
Keywords
Explainable opinion mining; Aspect-based opinion mining; Disinformation; Large language models; Hatred detection
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