Today, the Twitter engineering team released another very interesting Open Source R package for working with time series data: “AnomalyDetection“. This package uses the Seasonal Hybrid ESD (S-H-ESD) algorithm to identify local anomalies (= variations inside seasonal patterns) and global anomalies (= variations that cannot be explained with seasonal patterns).
As a […]
Open foresight is a great way to look into future developments. Open data is the foundation to do this comprehensively and in a transparent way. As with most big data projects, the difficult part in open foresight is to collect the data and wrangle it to a form that can actually be processed. While […]
Here’s another update on the analysis of Wikipedia data for the presidential candidates. What’s quite interesting, the attention value vor Mitt Romney is almost at the same level where Barack Obama has been four years ago. And Barack Obama is exactly where John McCain has been 2008:
But one thing has changed: The elections […]
Just a few hours before the ballots open for the 57th presidential election, the key question for us data scientists is: which data set could really show some special information, that would not be easily available through a classic poll. We have already seen some interesting correlations of Wikipedia usage with the ongoing campaign […]
Here’s an addition to my last post on using Wikipedia data to analyse attention for the US presidential elections 2012. Here’s another look at the interest not for the candidates’ Wikipedia pages but the general pages for the elections 2008 and 2012. Compared to the candidates’ pages, the attention for the general […]
One of the most interesting challenges of data science are predictions for important events such as national elections. With all those data streams of billions of posts, comments, likes, clicks etc. there should be a way to identify the most important correlations to make predictions about real-world behavior such as: going to the voting booth […]