ESSEM 2013 - 2013 International Workshop on Emotion and Sentiment in Social and Expressive Media: approaches and perspectives from AI

Social and expressive media can represent a challenge and a push forward for research on emotion and sentiment in AI. In fact, in such interaction contexts the subjective and expressive dimensions are predominant and open the way to the emergence of an affective component within a dynamic corpus of contents, created or enriched by users according to new paradigms of interactions fostering first-person engagement. This calls for delving into the evolution of approaches, techniques and tools for modeling and analyzing emotion and sentiment, with the aim of dealing with the cognitive and affective information conveyed by media reflecting spontaneous, multi-faceted and unstructured user responses. The workshop aims at bridging between communities of AI researchers working in the field of affective computing under different perspectives. Such perspectives include, on the one hand, research on models and techniques for sentiment analysis and opinion mining on linguistic corpora and unstructured data from social web; on the other hand, research on formal and cognitive models for the integration of emotional states in intelligent agents, or, in general, on the key role of emotions in multi-agent systems for what concerns both communication aspects and the definition of sophisticated emotion-aware coordination or negotiation strategies. We believe that cross-fertilization between different but related communities will be precious in order to face open challenges, in particular, the ones raised by the social and expressive media, such as:
investigating advanced social aspects of emotions, i.e. regulative or ethic issues related to emotions in virtual agents;
extracting concept-level sentiment conveyed by social media texts by relying on structured knowledge of affective information, i.e. affective categorization models expressed by ontologies, better still if psychologically motivated and encoded in the semantic web standards;
cross-validation between sentiment-based approaches and cognitive models;
fostering the interoperability and integration of tools by encouraging compliance with emerging standards.