From the post:
Today, we are excited to announce the release of our anonymized dataset that discloses the browsing behavior of hundreds of millions of users who engage with our content recommendations. This data, which was released on the Kaggle platform, includes two billion page views across 560 sites, document metadata (such as content categories and topics), served recommendations, and clicks.
Our “Outbrain Challenge” is a call out to the research community to analyze our data and model user reading patterns, in order to predict individuals’ future content choices. We will reward the three best models with cash prizes totaling $25,000 (see full contest details below).
The sheer size of the data we’ve released is unprecedented on Kaggle, the competition’s platform, and is considered extraordinary for such competitions in general. Crunching all of the data may be challenging to some participants—though Outbrain does it on a daily basis.
The rules caution:
The data is anonymized. Please remember that participants are prohibited from de-anonymizing or reverse engineering data or combining the data with other publicly available information.
That would be a more interesting question than the ones presented for the contest.
After the 2016 U.S. presidential election we know that racists, sexists, nationalists, etc., are driven by single factors so assuming you have good tagging, what’s the problem?
Or is human behavior is not only complex but variable?