A new open journal on Data Science
From the post:
Springer has introduced a new open, peer-reviewed journal focused on Data Science: EPJ Data Science.
What makes this a Data Science journal is novel uses of statistics, data analysis, computer techniques and public data sources to research a topic in another domain, rather than methodological research. Here are a few examples of the papers you'll find in the journal:
- A confirmation of the "Pollyanna Hypothesis" that we use more positive words than negative words (and so negative sentiments carry more weight than positive ones).
- An analysis of the Love Parade disaster, using photographs, satellite images, and public documents to investigate the causes that led to 21 deaths in a 2010 crowd panic in Germany.
- An analysis of politically-active Twitter users users that reveals that Republicans in 2008 had a more tightly-connected social network that was more effective at broadcasting political material on Twitter.
Unsurprisingly, many of the articles use the R language for the underlying analysis and data visualization. And because this is an open journal, you're free to read any of the articles at the link below.
Now that’s good news!