We are pleased to announce the release of our first research prototype of a social dynamic analysis tool for Wikipedia called WikiDashboard.

The idea is that if we provide social transparency and enable attribution of work to individual workers in Wikipedia, then this will eventually result in increased credibility and trust in the page content, and therefore higher levels of trust in Wikipedia.

This demo features the Wikipedia, with the text colored according to trust. Text on white background is fully-trusted text; the more orange the background, the lower the value of trust. Type a page title in the search box on the left to see the page trust-colored.

View real-time data and statistics from any logfile on any server with SSH, in an intuitive and entertaining way.

This Hierarchical Temporal Memory (HTM) technology has the potential to allow computers to solve problems that are currently easily solved for humans but difficult or impossible to solve for machines.

We'll call the "Kevin Bacon number" from one article to another the "distance" between them. It's then possible to work out the "closeness" of an article in Wikipedia as its average distance to any other article.

A mathematical model produced by Prof Andrew Watson suggests that the odds of finding new life on other Earth-like planets are low, given the time it has taken for beings such as humans to evolve and the remaining life span of Earth.

The concentric circles are news categories, expanding from least to most total word counts per category. The individual word counts of each story are plotted on the corresponding concentric circle, on a spoke of the corresponding page.

Strong competitors are generally thought to bring out the best in everyone, but what if the competition is so strong it makes the top prize feel out of reach? Can strong competition actually undermine a reward structure? A new study by Jennifer Brown of B

Most of these datasets are related to machine learning, but there are a lot of government, finance, and search datasets as well.

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