Social Data are generated by online systems, such as YouTube, Facebook, Flickr and Del.icio.us, where users store data and share experiences. In the recent years we have been witnessing the rapid development of online social websites and instant messaging systems. Due to the success of such systems, numerous web users everyday use the Web as a social medium to interact with other people and to share their experiences.

Social data mining is a new and challenging aspect of data mining. It is a fast-growing research area, in which connections among and interactions between individuals are analyzed to understand innovation, collective decision making, and problem solving, and how the structure of organizations and social networks impacts these processes. Social data mining includes various tasks such as the discovery of communities, searching for multimedia data (images, video, etc) personalization, search methods for social activities (find friends), text mining for blogs or other fora. Social data mining finds several applications; for instance, in e-commerce (recommender systems), in multimedia searching (high volumes of digital photos, videos, audio recordings) in bibliometrics (publication patterns), in homeland security (terrorist networks).

This workshop intends to provide a forum for researchers in the field of Data Mining, Machine Learning and Artificial Intelligence, to discuss the above and other related topics regarding Social Media.

Workshop Topics

Possible topics of the workshop include (but are not limited to):

* Social network analysis
* Bibliometrics
* Community discovery
* Personalization for search and for social interaction
* Recommender systems
* Web mining algorithms
* Applications of social network analysis
* Mining (Collaborative) Tagging Systems (blogs, wikis, etc.)
* Mining social data for multimedia information retrieval
* Opinion mining

Why the topic is of interest at this time?
User-centric content publishing and management Web applications (also known as Web 2.0 applications), such as wikis, web logs (blogs), and resource sharing systems, have been constantly developing and maturing in the last few years. Now that the hype of Web 2.0 is over, several limitations of social media have surfaced, such as information redundancy (synonymous tags), noise, ambiguity (polysemous tags) and spam. It is therefore now the right time for the application of sophisticated machine learning, data mining, information retrieval, information extraction, semantic Web and natural language processing algorithms that will improve the search for content, the navigation within the content and the overall user experience in these systems.