About |
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This special issue focuses on bringing multidisciplinary knowledge into sentiment analysis. We expect submissions that introduce theories not usually part of the standard sentiment analysis framework, and potentially attract researchers to learn more about the relevant literature. Minor improvements, e.g., a new neural network architecture that changes performance but lacks a rationale, and applications of the same method on a different domain or dataset fall outside the scope of this special issue |
Call for Papers |
Topics of InterestThis special issue focuses on emerging techniques and trendy applications of sentiment analysis as a multidisciplinary research area. Given the focus of the journal, we expect to receive works that propose new AI algorithms for the advancement of sentiment analysis research. While other disciplines, e.g., semiotics, psychology, linguistics, are surely welcome, the AI component must be there and it must be in line with the state of the art. Mostly, we expect to receive works on textual sentiment analysis, but papers on multimodal sentiment analysis will also be considered. The topics of this special issue include but are not limited to: - Critical assessments of existing sentiment analysis methods - Explainable sentiment predictions - Sentiment of multiword expressions - Hybrid symbolic and sub-symbolic AI for sentiment analysis - Theoretical foundations of AI for sentiment analysis - SenticNet 6 and other hybrid knowledge bases for sentiment analysis - Sentic LSTM and other hybrid deep nets for sentiment analysis - Commonsense reasoning for sentiment analysis - Semantic models for sentiment analysis |
Credits and Sources |
| [1] SAMRA 2021 : Sentiment Analysis as a Multidisciplinary Research Area |
