At the center of our vast, electro-digital journalistic infotainment ecosystem, there, hidden behind the more recognizable names of the products it owns, is Betaworks. As I wrote in April, the company has come to own, in the past year, many of the products which facilitate the distribution of news articles online: It owns Bit.ly, which shortens domain names and tracks their movement across social network. It owns Chartbeat, which tracks live user activity on a website. It owns Digg, and Digg Reader, a social news service and one of the web’s most popular RSS readers.
Betaworks also owns Instapaper, which it bought from the independent developer Marco Arment in the spring. Instapaper is one of the most popular of the read-it-later services, and it’s also the final stop for news articles shared on the web. Text goes there to be read in a clean environment — or, just as often, to die.
Today, we got a taste of what that ownership is letting it do, when Betaworks announced the first major update to Instapaper since Arment sold it. (In fact, it was Instapaper’s first major update since October 2011.) The app will now include a new, intriguing feature:
Our new Popularity sort is probably the most interesting feature in this update. We used a variety of Instapaper data signals (how many times an article was saved, how often it’s been opened, how often it gets read , and how many likes, saves, and shares it got from users) to calculate a popularity score for each article. Our algorithm then takes that data, applies some weighting and time decay functions, and ranks your queue.
In other words, Betaworks will use the data it collects from Instapaper users to figure out what’s saved and what’s actually been read. It’s putting to use what it can see inside the machine to help readers figure out what they most want to read. Algorithmic recommendations, famous on Netflix and Amazon.com, will now be in your quiet, read-it-later app — delivered on an article-by-article basis.
There’s already a news aggregation website which surveys social networks and offers, with some editorial assistance, interesting articles: It’s called Digg. With Instapaper, Betaworks will harness the tics of the crowd to recommend articles you’ve expressed an interest in to you personally. It’s kind of the algorithmic-editorial recommendation engine, long spoken of by Google and Facebook — except, here, you’re choosing what to throw into the mix.
It’s intriguing to think what might happen down the road, if Betaworks took the data from all these little silos — Instapaper and Bit.ly and Digg and even Chartbeat — and combined their power.