Contemporary social sciences are facing a serious paradigm shift because of the developments in computer and Internet technologies,though traditional social sciences are still very important.
Big data, such as digital traces of online activities and mobility records, allows us to quantify human behavior and social phenomena at a fine-grained level,yet it is global in scale, thereby complementing experimental data and theoretical and computational simulation results.
In some cases, we can even employ the methods of natural sciences, including physics,chemistry or biology, in order to analyze big data.
From this perspective, we will organize the workshop of “applications of big data for computational social science.”
The scopes of the workshop include the applications of big data, as well as the methods for collecting and using big data for computational social science.
Moreover, theoretical frameworks and computational techniques for big data are also very important topics in our workshop.
In this workshop, social sciences are not limited to sociology,economics, marketing, political science,but also include informatics, complexity science,econophysics,sociophysics, culturomics and the arts.
Real time analytics for heterogeneous spatio-temporal big data streams
Unsupervised machine learning for big data
Scalable predictive analytics workflows for big data
Extracting and visualizing critical insights from big data
Uncertainty propagation in connected big data models
12月05日
2016
12月08日
2016
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