The first objective is to study and quantify our knowledge about key aspects of the new media workflow driving the entertainment industry: the way the new generation of media producers work (professionals, independent, and amateurs); how they use new distribution mechanisms to accommodate user interests; how viewing communities are constructed and how producers conceptualize users’ engagement in this model. Existing social and market models (e.g., audience interests, publicity impact) are being updated constantly by new players.
The second objective addresses the production side of the new media workflow, more specifically the role of intelligent metadata and new digital formats in the production of video programs. The fast pace at which media is created puts an unprecedented pressure on the media producers who want their content to reach the target market as quickly as possible. An example of such a new paradigm is the TV series “Sanctuary”: it was filmed entirely in a digital set, which reduces the production time and costs, and it was first sold directly to the viewer on the Internet. In this new distribution environment, reaching the target market can be a difficult task. Thus, linking media production with new digital video formats to rich metadata is critical to reach the right community of viewers.
The third objective is to develop richer immersive environments and novel feedback mechanisms inferred from richer interactions with media and among viewers. Traditional feedback models capture viewing audiences and their points of access from which user profiles can be computed. These models provide an incomplete picture of the full spectrum of media consumption: richer feedback mechanisms using alternative channels such as SMS, Internet forums, and live chats between viewers and actors (e.g., popular TV shows such as Big Brother) are not yet systematically incorporated into the equation that enables programmers to serve audiences. This illustrates the exciting opportunities for exploiting the advantages offered by the community and personalized aspects of Internet services, and to strengthen TV producers and broadcasters’ most valuable asset: the viewers’ long-term loyalty.
Our fourth objective links the outcomes of the previous two objectives: it aims at improving the viewers’ experience by offering them a personalized combination of the mainstream TV content together with online user generated content. More specifically we will research algorithms that process the content metadata, the user and the community feedback to aggregate TV content and user generated content, thus, enabling users to access TV channels they are most likely to favor on demand. This will result in a win-win situation: viewers get personalized recommendations of popular content and TV broadcasters achieve more effective publicity.