Back in the December, I profiled the cadre of companies — ranging from Flipboard to SmartNews to News360 — that aim to be your one-stop mobile destination for news. While interviewing their founders and marketing teams, I listened as each company made claims as to the level of customization it offered, customization so refined you wouldn’t waste time scrolling through headlines that didn’t interest you. An app’s machine learning algorithm would monitor your browsing habits, and through this accumulation of data it could discern the unique elements of your taste and information needs.
But as I downloaded and tried out each app for myself, I found it difficult to detect any differentiating factor that led me to conclude the app had truly gotten to know me. Sure, I came across headlines that interested me, based in part on the broad categories I checked off when first launching the app, but the signal to noise ratio wasn’t any better than if I had visited the homepage of any major news publication. None of the apps became a daily habit in the same way that apps like Facebook, Twitter, and email compel me to open them whenever I’m staring at my phone.
The problem is that news tastes go beyond mere categories and keywords. Sometimes I read a piece not because it’s on a certain topic but because it was written by someone whose writing I admire. Other times I might be interested in coverage of a particular company, but only for specific aspects of it. I could care less about Apple hardware news but gobble up information about its various content and software plays on mobile. But clicking on an article about Apple’s streaming music service merely signals to the app I care about Apple and music (I actually hardly listen to any music). I’m not sure that any nuance beyond those broad categories is actually possible at this point.
The chief problem I have with many news apps is they don’t deliver the level of customization that I can get on Twitter, Facebook, and other social networks. I launched my Twitter account in late 2008. In the intervening years I’ve accumulated a list of over 700 people whom I follow, and for a significant portion of those people I wouldn’t be able to remember my reasoning for following them. In some cases they’re colleagues I’ve worked with. In others they’re writers and journalists I admire. But there are still plenty more I followed because something in their profile caught my eye or they authored an article I enjoyed but have long since forgotten.
But despite not having a complete understanding of all my follow choices, my Twitter feed is a well-oiled machine, one that produces a rich tapestry of news and commentary (and plenty of jokes) every time I open it. In addition to providing an excellent source of news aggregation, it also allows the people I follow to offer a layer of commentary over that news. They can improve upon headlines and unearth interesting stats that are buried deep within an article. These are features a machine algorithm, no matter how finely tuned, can’t duplicate.
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Since I wrote that article, a number of new news aggregation apps — including one from BuzzFeed — have entered the market. At least one major player, Circa, has ceased operation. And Apple itself is launching its own standalone app, this one likely to be featured as a default on the homescreen. It seems clear that Silicon Valley has convinced itself there is a market need for these news apps. But I find myself agreeing with Paul Cantor, who wrote a piece recently arguing that “nobody goes on the internet to read.” What he means is that nobody opens up an internet browser the same way they open a book or a magazine. They go to the internet as a point of reference, to seek out specific information or to be entertained. Yes, in the process of this browsing they may come across news articles and videos, but these are simply byproducts of a larger ecosystem that includes your friends’ baby photos, dispatches from Weird Twitter, and YouTube videos on how to install kitchen tile. To divorce news from these other offerings is to ignore the very reason we open apps or log on to social platforms. And no algorithm, no matter how personalized, can supersede that.
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