An Introduction to SFI’s Visiting Faculty

Three researchers are spending several months at SFI to tackle some big questions: “Why do we sleep less as we get older?” “What do city pigeons have in common with drug interactions?” and “Is there a trajectory underlying human history?” to name a few.

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New study improves 'crowd wisdom' estimates

In a new study, researchers examined just how accurate our collective intelligence is and how individual bias and information sharing skew aggregate estimates. Using their findings, they developed a mathematical correction that takes into account bias and social information to generate an improved crowd estimate. 

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Machine learning yields new insights into French Revolution’s early days

New research from an interdisciplinary collaboration among historians, political scientists, and statisticians suggests that rhetorical innovations may have played a significant role in winning acceptance for the new principles of governance that built the French republic’s foundation — and inspired future democracies around the world. 

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Social learning squared

A workshop, Integrating different perspectives on social learning, meets to share insights from a range of disciplines.

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Video: Damon Centola on 'How Behavior Spreads'

Damon Centola presents more than a decade of original research examining how changes in societal behavior ― in voting, health, technology, and finance ― occur and the ways social networks can be used to influence how they propagate. Watch the talk. (1 hour 22 minutes)

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Finding meaning in big data

The noise in high-dimensional datasets can obscure real correlations — and give rise to illusory patterns that don’t mean anything. April 2-5, an interdisciplinary group of mathematicians, physicists, and theoretical computer scientists meets at SFI to address the problem and devise new algorithms that can succeed all the way up to the limits that arise from not having enough data, or not knowing if the data is accurate.  

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