The transformation of the Web from its humble read-only origins to the
current interactive/read-write medium has made its users ever more keen to
share their sentiments and opinions through blogs, wikis, fora, chats and
social networks, giving birth to a sort of social affective intelligence
that emerges from the integration, competition and cooperation of web-users.

The distillation of knowledge from such type of social affective data is a
key factor for applications in fields such as commerce, tourism, education
and health, but the extremely unstructured nature of these contents and
their exponentially growing size make it a very difficult task.

Such a challenge requires the ability to both represent and perform
reasoning on social affective data, tasks which have been separately
undertaken by Semantic Web and AI researchers respectively, exploiting
techniques such as RDF schemas, triple stores, ontology languages, machine
learning, neural networks and computational intelligence.

The aim of this group is to bring these two complementary groups
together across the disciplinary divide for possibly the very first time,
exploring the new frontiers of opinion mining and sentiment analysis. « less