Emotion Recognition became a key scenario for artificial intelligence and data mining systems, as well as for social network analysis.
Various emotion-mining techniques can be exploited  for creating and automating personalized interfaces or subcomponent technology for larger systems, i.e. in business intelligence, affective tutoring, recommender systems, social robots.
Different from sentiment analysis, this approach works at a deeper level of abstraction, aiming at recognizing specific emotions and not only the positive/negative sentiment; in order to extract, manage and predict emotions in limited sets, based on novel models of emotions, or on well-accepted models e.g., the Ekman and Plutchik models.

The aim of the international workshop EMORE is to present, discuss and ideate new emotion recognition techniques in any AI-related task, bringing together researchers and practitioners for stimulating cooperation and cross-fertilization between different communities focused on research, development and applications of emotion recognition.

EMORE is a preliminar discussion forum for ACER (workshop on Affective Computing and Emotion Recognition at IEEE/WIC/ACM International Conference on Web Intelligence), and future events where the authors are also invited to submit novel researches on Affective Computing. Aiming at this collaboration path, EMORE also welcomes papers on ongoing projects and PhD showcases, as well as applications, data sets, novel techniques, and multimodal or interdiscipinar approaches to emotion recognition.