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NETWORKED:The New Social Operating System. Lee Rainie & Barry Wellman
MIT Press http://amzn.to/zXZg39 Print $14 Kindle $9
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Date: Mon, 27 Jul 2015 11:02:20 +0000
From: "[utf-8] Complexity Digest" <[log in to unmask]>
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To: "[utf-8] Barry" <[log in to unmask]>
Subject: [utf-8] Latest Complexity Digest Posts
Learn about the latest and greatest related to complex systems research. More at http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=dd1eded036&e=55e25a0e3e
The Social-Network Illusion That Tricks Your Mind
Network scientists have discovered how social networks can create the illusion that something is common when it is actually rare.
See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=6a23673b8c&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=3a4c237fbe&e=55e25a0e3e)
Evolutionary dynamics of collective action in spatially structured populations
Many models proposed to study the evolution of collective action rely on a formalism that represents social interactions as n-player games between individuals adopting discrete actions such as cooperate and defect. Despite the importance of spatial structure in biological collective action, the analysis of n-player games games in spatially structured populations has so far proved elusive. We address this problem by considering mixed strategies and by integrating discrete-action n-player games into the direct fitness approach of social evolution theory.
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Topological data analysis of contagion maps for examining spreading processes on networks
Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth˙˙s surface; however, in modern contagions long-range edges˙˙for example, due to airline transportation or communication media˙˙allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct ˙˙contagion maps˙˙ that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.
Nature Communications 6, Article number: 7723 http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=e9371eafa3&e=55e25a0e3e
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If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache...
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