Motivation of the Track
One of the most pressing, and fascinating, challenges of our time is in understanding the complexity of the global interconnected society we inhabit. The rapid growth of the Internet and the Web, the speed with which global communication and trade now takes place, and the fast spreading around the world of news and information as well as epidemics, trends, financial crises and social: these are all signals that mankind has entered a new era, a new techno-social ecosystem whose inner mechanisms are different from before, and largely unveiled. Ours is also a time of opportunity to observe and measure how our society intimately works: the big data originating from the digital breadcrumbs of human activities, sensed as a by-product of the ICT systems that we use, promise to let us scrutinize the ground truth of individual and collective behavior at an unprecedented detail. Multiple dimensions of our social life have now big data “proxies”:
Sensing big data at a societal scale, and the interlinking of digital and physical reality, is providing us with a powerful social microscope, which can help us understand many complex socio-economic phenomena. It is clear that such challenge requires high-level analytics, modeling and reasoning across all the social dimensions above. In practice, however, there is a big gap from the opportunities offered by the big data to the challenges posed by the social phenomena. The reasons behind the gap are at least the following. First, Analytics and data mining offer limited tools to study the models and patterns of human activities. Although
data mining from traditional databases is a mature technology, we do not have yet adequate data mining tools to deal with the networked, multi-dimensional nature of human activities and their semantic richness. The role of social semantics is confined to the preparation of data and to the interpretation of the obtained patterns and models, without truly high-level modeling tools. Second, people are unaware of the power of their personal data, which are predated by service providers and secluded in disparate public and private databases. Lack of trust and transparency makes people reluctant to share high-quality personal data. What is missing here? Social mining techniques and tools able to deal with semantic-rich data, complex data for extracting patterns and models, which incorporate the multi-dimensional aspects of real life taking into consideration possible ethical and legal aspects like privacy,
data protection, transparency and user control on own personal data.
The purpose of this track is to encourage principled research that will lead to the advancement of the data analysis, social mining and privacy-aware (big) data analytics.
Topics of the track
The track will seek top-quality submissions addressing important topics that include, but are not limited to, the following:
Technical Program Committee