In this talk, research and applications in social media mining and multimedia analysis are going to be presented. Social media sharing websites host billions of images and videos, which have been annotated and shared among friends, or published in groups that cover a specific topic of interest. The fact that users annotate and comment on the content in the form of tags, ratings, preferences and so on, and that these activities are performed on a daily basis, gives such social media data source an extremely dynamic nature that reflects topics of interests, events and the evolution of community opinion and focus.
The talk will present research challenges and activities and will focus on multi-modal graph-based community detection methods for social media mining, concept and event detection. Clusttour, a mobile and web application integrating research results with appropriate interface design will be demonstrated as a relevant use case. The talk will also include approaches for object/region classifiers learned using the self-training paradigm with loosely annotated training samples automatically selected from social media.