Suchergebnisse

'Many of us have stood above a colony of ants and been astounded at their ability to act and organise as a social system. Humans are, of course, smarter, independent free-thinking individuals. Read this book and think again. With eyesight sharpened by math, modeling, and the familiarity with a new landscape he has in part created, Sandy Pentland and his team are mapping out a new world, crawling with information, that offers some real understanding of who we are and who we could be. Welcome to the age of social physics.'

Drawing on a unique, multi-year collaboration with the heads of major IT, wireless, hardware, health, and financial firms, as well as the heads of American, EU, and other regulatory organizations, and a variety of NGOs [1,2],I describe the potential for pervasive and mobile sensing and computing over the next decade, and the challenges that will have to be faced in order to realize this potential. ; United States. Army Research Laboratory (Cooperative Agreement Number W911NF-09-2-0053) ; United States. Air Force Office of Scientific Research (Award Number FA9550-10-1-0122)

© Springer International Publishing AG 2016. Understanding political phenomena requires measuring the political preferences of society. We introduce a model based on mixtures of spatial voting models that infers the underlying distribution of political preferences of voters with only voting records of the population and political positions of candidates in an election. Beyond offering a costeffective alternative to surveys, this method projects the political preferences of voters and candidates into a shared latent preference space. This projection allows us to directly compare the preferences of the two groups, which is desirable for political science but difficult with traditional survey methods. After validating the aggregated-level inferences of this model against results of related work and on simple prediction tasks, we apply the model to better understand the phenomenon of political polarization in the Texas, New York, and Ohio electorates. Taken at face value, inferences drawn from our model indicate that the electorates in these states may be less bimodal than the distribution of candidates, but that the electorates are comparatively more extreme in their variance. We conclude with a discussion of limitations of our method and potential future directions for research.

An introductory statement by the editors of the present proceedings, detailing the symposium itself as well as its peer-review process and acceptance rate, a summary of the included papers, and details on the editors themselves.