Ever since the web first started to become mainstream, there have been attempts to build the “Daily Me,” a personalized newspaper that learns what you like or are interested in (does anyone remember PointCast?). But as I noted in a recent post on the topic, many of these efforts are lackluster at best, and irritating at worst. They either require too much fiddling to tune them, or they don’t show any intelligence at all (or both). But that doesn’t stop companies from trying — and the most promising entrants in this race so far are those that try to build their recommendations on top of the social signals coming from Twitter and other networks.
The latest to join the field is a personalized magazine app for the iPad called Zite, whose name is a play on the German word “zeitgeist,” meaning “the spirit of the times.” The company behind the app is based in British Columbia, and has been funded by angel investors and research grants from the Canadian government. CEO Ali Davar says Zite has been working on its recommendation engine for several years. An earlier version of the project, which is based on technology developed at the University of British Columbia’s Laboratory for Computational Intelligence, involved a browser extension called Worio that suggested related results when users did a Google search.
The Zite app pulls in your Twitter account and your Google Reader feeds (if you have them), then suggests topics based on your interests. This was the first place where it fell down for me — it said that it didn’t have enough information about me, which I thought was odd, since I have been on Twitter for about four years, have posted more than 35,000 tweets and follow over 2,000 people. I’ve used Google Reader for years as well, and am subscribed to about 600 feeds. Although Zite got some of its suggestions right, it recommended Barcelona as a topic, which was totally out of left field — in fact, I can’t recall ever mentioning the Spanish town before.
Although Robert Scoble says Zite doesn’t feel as slick as Flipboard, I thought the app worked quite well in terms of usability — you can swipe to move through articles, click to read them in a built-in browser, and share them easily (although you can’t save them to Instapaper, which is a shame). And you get asked with each one whether you like the content or want to see more of it, which is something other apps and services such as Flipboard are missing. It requires some effort on a reader’s part to do this training, and many probably won’t do it, but it is crucial for learning likes and dislikes.
One glaring omission from Zite is the lack of Facebook integration. Davar says Facebook tends to provide sources that are too heterogeneous (that is, too diverse) to be a source of good recommendation data, and that might be true, but it’s still a giant social network and a huge part of many people’s online news consumption, so it seems odd to leave it out — especially when the data coming from the billions of “like” buttons scattered around the web could be a source of so much data on what people want to read (Yahoo Labs has just released an interesting survey of what that information shows about the popularity of news at some major websites).
There’s one nagging question that keeps jumping out at me as I look at all of these apps and services, however, and that is: Where is Google? The combination of smart aggregation and algorithm-driven personalization seems like something the search engine should be all over. Google News has added some personalization aspects, but they are anemic at best, and one of the original customized news-readers — Google Reader — hasn’t really capitalized on that opportunity much at all (although it does provide some recommendations for readers related to new feeds).
The reality is, the RSS reader has been eclipsed (for the small proportion of the population who even used one) by Twitter and Facebook and other social news sources, or smart aggregators such as Techmeme and Mediagazer. Google has more or less failed to take advantage of that transition at all when it comes to news reading, although it is trying to add social signals to search. Why not take FastFlip and try to make it a Flipboard or Zite or News360 competitor?
And apart from the Washington Post‘s new Trove project and the News.me spinoff from the New York Times that Betaworks is close to launching, newspapers — who should know a thing or two about filtering and recommending the news to people — are virtually nowhere in this game.
If there’s one thing that web users need more than ever, it’s smart filters to help them navigate the vast tsunami of information that comes at them every day. (The big problem isn’t information overload, says Clay Shirky, but rather “filter failure”.) Someone is going to solve that problem, and if they do it properly, they could wind up capturing a significant share of the online news-reading market.
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