Topics of interest

Includes but not limited to:

  • Ontologies and knowledge bases for emotion recognition
  • Topic and entity based emotion recognition
  • Semantics in the evolution of emotions within and across social media systems and topics
  • Semantic processing of social media for emotion recognition
  • Contextualised emotion recognition
  • Comparison of semantic approaches for emotion recognition
  • Personalised semantic emotion recognition and monitoring
  • Using semantics for prediction of emotions towards events, people, organisations, etc.
  • Baselines and datasets for semantic emotion recognition
  • Semantics in stream-based emotion recognition
  • Comparison between semantic and non-semantic approaches for emotion recognition
  • Multimodal emotion recognition
  • Multilingual sentiment analysis
  • Challenges in using semantics for emotion recognition
  • Retrieval of emotion-based documents from repositories
  • Deep learning and knowledge-enabled approaches for sentiment analysis
  • Big Data tools and techniques for sentiment analysis
  • Applications of sentiment analysis within specific domains (e.g. health, robotics)