Blog Post

Everyone wants to be a news filter now

As the avalanche of information coming through social networks and real-time tools like Twitter continues to grow, the need for filters to make sense of that tsunami of data also increases, and it seems as though everyone has a different way of trying to solve that problem. Facebook threw its hat into the ring this week with what it says is an improved “newspaper-style” news feed that highlights important content, while Digg has just launched “newsrooms” aimed at doing the same thing, and online influence-ranking service Klout is rolling out topic pages based on what’s being shared by those with influence. But will any of these be able to solve the filtering problem, or will they just add another source of noise?

Facebook says that its changes (which my colleague Colleen covered for GigaOM) are designed to create “your own personal newspaper” when you log in to the social network, by showing you what the site believes are the most important items at the top of your news feed. In effect, this merges what Facebook used to call “top news” — which you previously had to select from a drop-down menu — with your regular news stream. And Facebook is also going to use its algorithms to show you different items based on when you last logged in to the site, so that what you see is always “new.”

When you pick up a newspaper after not reading it for a week, the front page quickly clues you into the most interesting stories. In the past, News Feed hasn’t worked like that. [Now] News Feed will act more like your own personal newspaper. You won’t have to worry about missing important stuff. All your news will be in a single stream with the most interesting stories featured at the top.

Facebook wants to be your newspaper

The repeated use of the term “newspaper” makes it obvious that Facebook wants this new feature to be about more than just seeing updates from your friend’s birthday party — and it could become especially interesting when combined with another new Facebook feature: the launch of the “Subscribe” service, which allows users to follow and get updates from people or sources they are not friends with, in much the same way that Twitter does. Facebook has been promoting that feature as a way to stay connected to what celebrities and journalists are doing, and it seems likely that many of those items could wind up on the top of your “personal newspaper” thanks to the news feed changes.

Digg, meanwhile, also seems to be betting that it can help sort the news for people via what it is calling topic-based “newsrooms” — and that launching this kind of option might help restore some of the site’s faded glory, which took a beating after a disastrous relaunch in 2010 that caused many users to flee. One of the elements of that redesign was a focus on news from mainstream sources such as traditional media outlets, which seemed to irritate many long-time Digg fans. The “newsroom” launch takes a different tack: instead of allowing media outlets to plug their RSS feeds directly into Digg, the service is creating pages that will feature content that has been shared by highly-ranked users.

This is similar to what Klout is trying to do with its topic pages, which the site says are currently in limited beta, but will be rolled out to all users soon. While Digg is basing its “newroom” content on what gets shared by users who are ranked highly by other members of Digg, the topic pages at Klout are created from content shared by those who the service’s algorithms have determined have a lot of influence about a certain topic — based on their activity on Twitter, Facebook, Flickr and other social networks (including Google+, which the service just recently started including in its rankings).

Relevance is a tricky problem to solve

For me, both the Digg and Klout approaches suffer from the same kind of problem that many other filtering services do — including iPad apps such as and Zite, or web-based services such as Summify: either they are filled with the same content I’ve have already seen in other places, or the links simply aren’t relevant. Klout’s topic pages in particular contain all kinds of things that are barely even related to the topic, although that could be because they are still tweaking their algorithms. And recommendation systems are one of those things that can seem almost useless even when they are getting a lot of things right, because the parts that are wrong are so glaringly obvious.

As for Facebook’s attempt to create a “personalized newspaper,” the biggest issue for Facebook is that it is still used primarily as a social network for connecting with friends and family, and so doesn’t function as a real-time news and information network in the same way that Twitter does — or rather, it is a news and information network, but that news is still primarily personal. There’s a place for that, obviously, but it doesn’t really help filter the “news” in a broader sense. The launch of a subscription feature is clearly an attempt to move Facebook in that direction, but so far — as I’ve argued before — Twitter still seems to be winning that particular game.

It’s good that plenty of services are trying to solve the news-filtering problem, and different users may choose different solutions: for some, Twitter will be the best because it is brief, while others might prefer Google+ or the summaries that they get once a day from services like Summify or an app like AOL’s Editions. So far, no one seems to have come up with the one-size-fits-all solution to this modern dilemma.

Post and thumbnail photos courtesy of Flickr users Arvind Grover and Zarko Drincic

15 Responses to “Everyone wants to be a news filter now”

  1. The amount of news aggregation and curation tools is immensive, thats really true. If I had known this earlier I wouldn’t have started which simply takes twitter (and some geeky networks) and creates a summary from that ranked by retweets. So this is not really different to the other services, but one feature of jetslide is very important for me: being able to define keywords which should be boosted to the top of my summary – and even if the news containing the keyword did not occur in my twitter friends network.

    Another news service which I definitely recommomend is Often very relevant content for me.

  2. vancouver gadgets

    It seems to me that “solving the news-filtering problem” was solved about 100 years ago by the newspaper conglomerates. We just have to realize that what we see on Facebook and Twitter is not news but simply conversations and clutter for the most part. Do we really need to sort all this? If a Facebook post of a cat video comes up on top due to 100 likes is it really compelling news? To me – sorting things like Facebook and Twitter is the same as sorting a chatroom. Why bother? The whole point of entering a chatroom interface is the serendipity part of it as Chris alluded to.

  3. Jack Humphrey

    Algorithms will never trump human curated content. All news aggregation is pretty much the same. Sometimes it can be pretty good on a personal-use level, but people will rely on actual people to curate and bubble up the best news.

  4. Edward Agyeman

    Good read. I agree with you–that Facebook trying to transform into a “news network” is totally wrong. I get the subscribe function and all, that was genius. But that should have been it. Facebook is the most interpersonal network out there and that’s their bread and butter, moving away from that is just not smart.

  5. Robin Campbell

    It’s unlikely there will be a one-size-fits-all solution because everyone’s preferences and consumption behaviors differ. People tend to use 2-4 mediums a day to absorb their news and the battle is to be in one of those top spots.

    Each service is going for a different segment, so when you say the problem is that services are “filled with the same content I’ve have already seen in other places, or the links simply aren’t relevant,” you may be missing the use-case of that service. Not everyone has time or wants to surf Twitter all day.

    The battle is for the busy users, the people that don’t actively log in to twitter, or that have prioritized other things to do with their time. There are 400M users on Twitter and only 100M active – those lurkers and content consumers are up for grabs.

    Some people want a never ending stream of news – there are apps for that.
    Some people want a finite summary – there are apps for that too.

    Robin from @Summify

  6. I don’t think there’s a solution at all, although I appreciate the attempts (and I may be proven wrong one day). In order to begin to be effective, a filter needs to understand 1) what I’m interested in and 2) what I’m *going* to be interested in.

    Re: #1, even the most intelligent filter needs input data from me in the form of choices. However, that same filter is usually responsible for set of choices I’ve been given so in some cases the results can be self-fulfilling.

    Re: #2, we love serendipity. We often don’t know we are interested in something until we’re exposed to it. Not all interests are interrelated. Heck, I didn’t even know I would enjoy this article (enough to comment on it!) until I saw the link from a human source (@jayrosen_nyu).

    Someone may figure out the algorithm but it actually sounds kind of boring to me.

  7. jonathanstray

    I suspect that the key to “solving” the filtering problem is defining what the result SHOULD be. To put it another way: how to do judge whether any given filtering system — each of which may be a combination of individual human judgements, collective activity, and/or algorithmic special sauce — is better or worse than another?

    We can expect that there will be many different types of filters, specialized for different needs. Certainly a filter should be personal. But even in the case of a single individual, I feel like we do not currently have concrete answers to the question, “how could this filter be better?” Words like “relevance” and “breadth” are markers that hide our ignorance here.

    This problem of defining better filters is both philosophical/social, and technical/practical. It has to meet our value systems of “good” and it also has to be something that can actually be implemented.

  8. Mike Lizun

    I use them all, and still enjoy discovering news and finding stories myself via Google Reader. RSS is actually more important for me now than ever. With everyone sharing only the most popular stories, and algorithms created to offer me much of the same, you still need to go out and hunt for the stories that haven’t yet been discovered. Written by humans, discovered by humans, then, perhaps, curated and shared by humans. Oh, and don’t forget email! A lot of good stuff is still shared and sent that way, too.

  9. Jason Thibeault

    So the issue is not about relevance or aggregation. I want both. Whether it’s from Facebook or Klout, I don’t care. The issue is that I want more than just news. I imagine a service sometime in the future that provides me two things. First is a feed of the news that’s important to me (that I’ve indicated is important and that is being curated for me based on reading behavior). There are already services out there that provide this. Second, and more important to me, is the conversation AROUND the news. The opinion. The thought. The speculation, imagination, digestion, and discussion. Because even within a generic aggregated news stream there are stories I don’t care about. I just scan the headlines. When I want to read the story, I click on it. What if this service was a three-pane approach. First pane is aggregated news links. Second is the story itself (from the link I click). Third is the discussion around the story (from social media, from other news stories writing op-ed about the news story, etc.). If I click on a story and very little appears in the third column, it’s probably not very interesting news so who cares. This would be a truly useful and beneficial service to culling or curating news because it would help me better predict, at first glance, what might be interesting to read vs. skipping over.


  10. Kevin Marshall

    probably not a ‘one size fits all solution’ as the problem is different for everyone (so the solution must be different as well).

    It’s not just a news filter, or even just a recommendation engine…it’s got to be a ‘personalized’ discovery engine…and that’s what is (and why we are really diff. from all the other approaches you listed above).