The focus of SocialCom is on information and communication technologies aimed at modeling, analysis and synthesis of social interactions. The program will cover the whole spectrum of contexts where computers play a role in human-human and human-machine interaction, from co-located, face-to-face dyadic interactions up to large-scale on-line social networks. Submission deadline: May 18, 2012.

The 2012 edition addresses PhD students and young researchers to the forefront of research activity on data mining and modeling of complex techno-socio-economic systems. Recognized authorities in the field will give formal lectures tailoring these for an interdisciplinary audience. Participants will also have the opportunity to present the results of their research during a short communication session. As a whole, the planned summer school will allow participants to be exposed to cutting edge results in one of the most challenging research area, while at the same time enjoying the relaxing atmosphere of one of the most beautiful italian islands.

Social life is increasingly characterized by interdependencies among actors, which give rise to self-organization, feedback-loops, unpredictable and unexpected system behavior, and other complex dynamics. Providing novel and fast ways through which the behavior of individuals may have implications for the behavior of others, information and communication technologies (ICT) seem to dramatically emphasize these tendencies. Agent-based modeling promises to be a major tool for a better understanding of such complexities that fundamentally challenge the way social phenomena are approached. The workshop invites poster contributions of cutting-edge research that draws on such techniques or on empirical data tostudy interdependencies in social life, with a special focus on techno-social systems.

The candidate's areas of interest should revolve around individual and collective animal behavior, animal cognition, animal movement, human social behavior, social transfer of information, and/or the development of new methods (GPS, RFID, computer vision, etc.) to collect and analyze large scale behavioral data. Candidates with experience in experimental work (lab and field) and/or theoretical work are welcome, as well as candidates with an engineering background but a demonstrated interest in biology, in particular the research areas mentioned previously.

Recommender systems have been recognized as a promising way to solve the information overload problem, whose main task is to find out what their users might like. Recent evidence demonstrates the significance of social influence and indicate that recommendations made by advanced techniques and algorithms are often less appreciated than those coming from our friends or acquaintances. The emergence of large-scale social network services, such as Facebook and Twitter, is facilitating the development of social recommendation. We seek high-qualified, original submissions of reports on research covering all the aspects of designs, techniques, algorithms, experiments, and empirical analyses on social recommender systems.