6th ICSADL 2027 invites original research contributions that address the recent research advancements and challenges in the field of sentiment analysis and deep learning. We encourage submissions that explore the intersection of these two fields and their applications across various domains.
♦Sentiment classification, polarity detection, and opinion mining
♦Aspect-based and fine-grained sentiment analysis
♦Emotion recognition and affective computing
♦Multilingual and cross-lingual sentiment analysis
♦Sentiment analysis of social media and text data
♦Multimodal sentiment and emotion analysis
♦Natural language processing and understanding
♦Large language models and transformer-based models
♦Explainable and trustworthy sentiment analysis
♦Sentiment analysis for human-computer and human-machine interaction
♦Domain-specific sentiment analysis
♦Fake news, misinformation, and opinion analysis
♦Deep learning architectures and neural networks
♦Transfer learning and representation learning
♦Generative AI and foundation models
♦Large language models and multimodal AI
♦Explainable, trustworthy, and responsible AI
♦Machine learning and computational intelligence
♦Big data analytics and knowledge discovery
♦Data mining and feature engineering
♦Intelligent data visualization and analytics
♦Statistical and predictive analytics
♦Edge AI and distributed intelligence
♦AI-based decision support and intelligent systems
♦AI and deep learning for industrial applications
♦Industrial data analytics and intelligent decision-making
♦Industrial IoT and edge/cloud-based intelligence
♦Industrial cyber-physical systems and digital twins
♦Intelligent manufacturing and Industry 4.0/Industry 5.0
♦Predictive maintenance, monitoring, and anomaly detection
♦AI-enabled industrial automation and control
♦Intelligent robotics and human-robot interaction
♦Human-machine interaction and human-centered AI
♦AI for industrial inspection and quality assessment
♦Computer vision and intelligent sensing for industrial systems
♦Explainable and trustworthy AI for industrial applications
♦AI for smart healthcare, transportation, energy, and smart environments
♦Data-driven optimization of industrial processes