Second International Workshop on
Modeling, Managing and Mining of Evolving Social Networks (M3SN)
Co-located with IEEE ICDE 2010

Welcome to M3SN 2010!

Motivation and scope

Online social networking is quickly turning into an popular means of interacting with friends, sharing information, finding information as well as people with common interests, and, in general, a way to manage ``personal spaces''. Online Social networking services of all flavors have grown remarkably in a short span of time, with millions of users creating and sharing a vast amount of data ranging from blog entries, bookmarks, pictures to interactive games and personal interactions.

The amount of attention the research community has devoted to social networks has so far not kept up with their growth in popularity and overall importance. This needs to be addressed as social networks give rise to a number of new research challenges unique to them, such as modeling and exploiting their evolutionary dynamics, effective resource discovery within the variety of ``social media'' (photos, blogs, videos, maps, games, etc.) exploiting the number of interaction paths available, engineering of the mining algorithms required to deal with the underlying, heterogeneous data making up social networks, etc.

Adaptation of existing approaches in search and advertising to social networks is not straight-forward as well: the standard advertising models used in the context of sponsored search appear to break down when applied to social networks and searching for people, contacts or shared interests is very different from the search over documents studied in information retrieval. Exploiting the profusion of information within the social network requires deeper collaboration amongst research areas as diverse as graph theory to sociology to economics, with effective data engineering methods to assure scalability of the resulting methods.

In this workshop, we aim to address some of these open research challenges in modeling and mining of dynamic social networks. In particular, we focus on research related to the following topics:

Topics of Interest

  • Modeling of Social Networks
    •  Evolutionary models for social networks.
    •  Privacy and security issues.
    • Modeling trust and reputation in social networks.
  • Recommendation
    • Importance of friendship links in social recommender systems.
    •  Impact of recommendation models on the evolution of the social network.
    • Classification models and their application in social recommender systems.
  • Advertisement models
    • Influence models and their application in social environment.
    • Social advertising.
    • Use of social networks for marketing.
  • Search in social media
    • Web page ranking informed by social media.
    • Expertise discovery.
    •  Collaborative Filtering.