Multimedia tools and applications are flourishing faster than ever, as mobile and social media platforms became ubiquitous in the current decade. The rise of tablets and smart phones has enabled users across all age to easily create, share, and consume multimedia contents. At the same time, people are increasingly dependent on social and cloud services for obtaining information while they are on the move. While it seems like a straightforward correlation of supply and demand to sustain the rapidly growing multimedia data, there are many challenges and limitations that prohibit the full realization of its potentials. Mobility and social requirements for emerging applications, such as health, transport, intelligent environment, and adaptive community, drive the need to innovate the solutions for semantic extraction, indexing, summarization, and delivery of context-aware services. Social Multimedia refers to multimedia content generated from social networks and is considerably rich in meta-data information, including location of content capture, camera properties, user profile information from the social network, and textual descriptors (e.g., hash tags on Twitter). Such meta-data provides a natural context to multimedia, shrinking the semantic gap between the information that one can extract from visual data and the interpretation that the same data holds for a user; thus enabling improved content analysis.

A Social Multimedia Signal presumes human users as sensors and contains the spatio-temporal activity pattern of users with respect to some multimedia content. However, human interactions are known to be extremely diverse and often inconsistent, tailored at deep cognitive levels. Therefore, social multimedia data is inherently noisy - every social interaction/activity cannot be deemed worthy of bearing adequate information to contextualize the related media. Sampling, estimation and analysis of social multimedia signals could provide valuable information about spread of shared multimedia, communities that have affinity to some category of multimedia and temporal evolution of the social network.

This workshop aims to congregate researchers, developers and business (advertising/marketing) individuals to share their experiences, achievements and vision in exploring the potential of social multimedia signals collected from social network data, augmenting traditional multimedia and inventing novel frameworks of media collaboration through social signals.