srs 2012 - 3rd International Workshop on Social Recommender Systems

While the abundance and popularity of social media sites allow people to leave and share their own digital footprints, they overwhelm the users with mountains of information and hence pose a great challenge for users to best leverage such information. Social Recommender Systems (SRSs) aim to alleviate information overload over social media users by presenting the most attractive and relevant content, often using personalization techniques adapted for the specific user.
This workshop aims at bringing together researchers and practitioners around the emerging topics of recommender systems within social media in order to: (1) share research and techniques used to develop effective social media recommenders, from algorithms, through user interfaces, to evaluation (2) identify next key challenges in the area, and (3) identify new cross-topic collaboration opportunities. To take advantage of the UMAP setting, we are in particularly encouraging two research sub-topics of the area: 1) Studying new techniques for user modeling to cope with recommendations in the social media 2) Studying different forms of people recommendation, including recommending people to connect with in social network sites, people to follow in real-time web applications, strangers who might be of interest, or people who may be interested to join online communities
Topics of interests include, but are not limited to:
Social recommender technologies and applications
User modeling techniques and their impact on social recommender systems
Recommendations for individuals and communities and their applications
Social recommender systems in the enterprise
Diversity and novelty in social recommender systems
User interfaces in social recommender systems, especially in recommending people and communities (SRS)
Transparency and explanations in SRS
Adaption and personalization for SRS
User feedback in SRS
Trust and reputation in SRS
Social awareness and visualization
Evaluation
Evaluation methods and evaluations of SRS
User studies
Special focus area: people recommendation
Recommending people to connect with or follow in social media sites
Recommending people for communities
User modeling for people recommendation