The concept is not new — based on what you click on, read, review or share, certain websites have the ability to store that information and base recommendations for you on it.
What is new is that this week The New York Times joined the group of websites that provide this service.
With news happening and being reported at rapid speeds, taking advantages of services like this can be beneficial to journalism students who try/need to keep up with current events. As New York Times lead technology reporter Nick Bilton Tweeted, the recommendations function is intended to help readers “see through the news fog” which can often become overwhelming.
The new feature lists 20 suggested articles that are based on sections and topics you most often click on, rather than keywords like many other sites are doing. Another difference: none of the recommendations come from personal information (like some sites use for advertising purposes). On the NYT website, all recommendations come directly from patterns that you create from your reading habits, and have nothing to do with any sort of patterns or information gathered from your online list of friends.
If you happen to use the NYT iPhone app, you’ll notice that the site recognizes if you click certain stories on your phone too, and those topics and sections you’re reading on the go will also be incorporated into the recommendations list when you check online.
Here’s a screen shot of what the recommendations list looks like now on the New York Times page: