R 3.1.1 (codename “Sock it to Me“) was released today! You can get the latest binaries version from here. (or the .tar.gz source code from here). The full list of new features and bug fixes is provided below. Upgrading to R 3.1.1 on Windows If you are using Windows you can easily upgrade to the latest version of R using the […]
Roughly a year ago I published an article about parallel computing in R here, in which I compared computation performance among 4 packages that provide R with parallel features once R is essentially a single-thread task package.
Roughly a year ago I published an article about parallel computing in R here, in which I compared computation performance among 4 packages that provide R with parallel features once R is essentially a single-thread task package. Parallel computing is incredibly useful, but not every thing worths distribute across as many cores as possible. Actually, […]
Apache Spark might push MapReduce to the back burner faster than some people might like, but it will also boost the Hadoop overall ecosystem. The project’s co-creator Matei Zaharia explains why Spark is so popular now and where it fits into the big data ecosystem.
Algorithms are a fascinating use case for visualization. To visualize an algorithm, we don’t merely fit data to a chart; there is no primary dataset. Instead there are logical rules that describe behavior. This may be why algorithm visualizations are so unusual, as designers experiment with novel forms to better communicate. This is reason enough to study them.
Using human evaluation of 100,000 words spread across 24 corpora in 10 languages diverse in origin and culture, we present evidence of a deep imprint of human sociality in language, observing that (1) the words of natural human language possess a universal positivity bias; (2) the estimated emotional content of words is consistent between languages under translation; and (3) this positivity bias is strongly independent of frequency of word usage. Alongside these general regularities, we describe inter-language variations in the emotional spectrum of languages which allow us to rank corpora. We also show how our word evaluations can be used to construct physical-like instruments for both real-time and offline measurement of the emotional content of large-scale texts.