On Thursday, Facebook outlined some of its platform roadmap plans for developers. One of the items on the long list was called the “Open Graph API“, and with such a name it was sure to raise some interest.
Details were scarce, but the general message coming out of Facebook is that the Open Graph API will allow any site to embed a Facebook page in it, allowing the site owner to set status messages, share links etc., without visiting Facebook itself, and more importantly without sending its visitors to Facebook.
That sounded like a feature aimed primarily at brands, or as Ethan Beard of Facebook presented it: “This will be good for brands like Coke.” Makes perfect sense, as these brands are already using Facebook as part of their social media efforts, but would prefer to have it done on their site rather than on Facebook itself.
Thinking deeper into where Facebook is heading, though, I would think there is a more major endgame to all this. We already know that Facebook wants us to consider it as our online identity. So it allows you to reuse that Facebook identity on other websites and sign in using Facebook Connect. That’s one side of the coin. And then the other side of it is, you have your own website or blog where you may publish thoughts, links and photos that you didn’t publish on Facebook. Facebook would clearly want to bridge that gap as well.
Half a year ago, Facebook adopted the emerging Activity Streams standard for publishing and consuming an individual’s lifestream events to lifestreaming frameworks, a standard promoted by open standards evangelist Chris Messina. So that fits in nicely into the puzzle now: wouldn’t it be nicer if you could publish all this non-Facebook activity into your Facebook’s page, which will now be embedded into your personal website, courtesy of the Open Graph API?
The API then is just the funnel through which your activity stream is published back into Facebook. You get to leverage the social graph you already defined and came to like on Facebook, and Facebook gets tighter integration with your life outside of Facebook, if you still had any. Smart move for Facebook.
Dare Obasanjo has an interesting post, with a good comments thread, on overflowing feed readers. He’s quoting from a post by Farhad Manjoo on Slate:
You know that sinking feeling you get when you open your e-mail and discover hundreds of messages you need to respond to…
Well, actually Dare’s post is from two weeks ago. The reason I got to read it only now is exactly that…
Yes, I know I don’t really need to ‘respond’ to subscriptions, and the answer should be – unsubscribe, or go on a feeds (or ‘follow’ edges) social diet. But these binary decisions are not always optimal, as I have plenty of feeds I subscribed to after hitting one or two posts I really liked, but that were not on that author’s main subject (if such exists at all). Thus I have to skim through many un-interesting (for me!) posts, many of them somehow always end up discussing twitter. In fact, that’s how most of my feeds look like (including the twitter part).
We need shades of grey between subscribed and unsubscribed. It would be great to have a feed reader that learns from how you use it. It should be quite clear which posts interest me – ones I took time to read, scroll through, press a link etc. – and which did not. Now train a classifier on that data, preferably per-feed (in addition to a general one), and get some sense of what I’m really looking for.
Now, I don’t need this smart reader to delete the uninteresting ones, let’s not assume too much on its classification accuracy. Just find the right UI to mark the predicted-to-be-interesting items (or even assign them into a special virtual folder). Then I can read these first, and only if/when have time – read the rest.
I assign this to be my pet project in case I win the lottery next week and go into early retirement. Alternatively, if someone saw this implemented anywhere – let me know!
Update: a related follow-up post on a new filtering product I started using.
As I wrote previously, I really like the idea behind Aardvark (previously known as Mechanical Zoo) and it’s a great social Q&A tool, but it simply is not “social search” (and unlike TechCrunch, RWW realize that). The Aardvark team still pushes with that terminology, I guess for a good reason given the financial climate, and disperses more of it in a white paper. Once they actually start searching in their aggregated Q&A repository to provide you with an available answer without bothering your network – that would become more of a search solution, rather than Q&A.
Having played with the product a bit, I also see an inherent flaw in the social premise here. Aardvark provides me with answers from friends, or friends-of-friends. Now, it’s more likely I’ll get answers from friends-of-friends, as there are simply a lot more of them. However, these would be people who don’t know me, and will not provide a personal answer that is tailored to my own individual needs.
Still, it’s a great way to make new friends. Not kidding – Aardvark strongly drives conversations, as Danny Sullivan also pointed out, and since this friend-of-friend was the one who responded to my question, I’d feel more comfortable discussing further. Presumably Aardvark will also track this, and practically add this person to my direct social graph.
Update: Max Ventilla of Aardvark commented in my previous post that indexing your graph and finding the right person to answer your query has, in fact, the ingredients of social search. He has a point there, but still that search ends in finding a person, not information, so it’s more of a people search. Still, I agree that in executing this task, the varkers face similar difficulties to those we faced in Delver, albeir on much smaller scale.
This morning I came across a nice little people search demo by Martin Atkins. It’s mainly a wrapper over Social Graph API, but helps illustrate the public social graph. Now, Tantek Çelik is one of the main advocates for Microformats, which in turn generate a lot of the XFN data that feeds SGAPI. So it was quite a surprise to feed his name and see this:
The horror! the horror!!
What happened here? a quick check on SGAPI led to some strange findings. Turns out that Robert Scoble’s old blog at scoble.weblogs.com is listed as strongly conncted to Tantek’s blog identity. I then went on to check out that blog – no XFN or FOAF to Tantek there. So where did that come from?
A more elaborate dive into SGAPI’s more detailed output showed that Scoble was listed as referencing Tantek with both XFN attributes of “me” and “met“. In plain English, this means that Robert Scoble said “I am Tantek Çelik, plus I also met him in person!”. So what could cause this, except for some serious case of schizophrenia?
My humble guess is that Scoble, some time ago, listed Tantek as a “met” contact on his old blog, but with a magnificient little typo, left out the ‘t’. He then discovered the mistake and fixed it. But the Googlebot caught both cases, and added them both as relations. Now why would they do that? shouldn’t new data replace old data? well, that’s what other users of SGAPI are asking, see the discussion over at the group. Turns out the SGAPI data is not yet as timely as the main index, and Brad Fitzpatrick promises this will improve soon enough.
Considering the upcoming social diet, it better will…
Update: Hadar pointed out another example, where Chris Messina gets identified with TechCrunch UK… it’s indeed reflected in SGAPI, and I tracked this down to erroneous XFN tagging in an obscure 2006 TCUK post. Indeed demonstrates a weakness of the unmoderated, inherently decentralized XFN-based graph building. Still, for now it’s the only open standard we have, until some higher, post-processing open layer will emerge.
‘Tis the season for predictions (and Schadenfreude over last year’s).
One of the most popular predictions for the social web seems to be a diet.
One talks about “Social graph shrinkage“, another about “Social Media Indigestion” (both taken from Peter Kim‘s collection of Social Media Predictions 2009), and ReadWriteWeb adds “Friend List Sanitizers” into the whirlwind of diet buzz.
The reason I see sense in this prediction is one – Facebook Connect. So far, we knew what to expect as a result of too many Facebook friends. There was a certain volume of activity stream, and we managed to live with it. With significant adoption of Facebook Connect (which is the main if here), we’ll soon start seeing many external activities being pushed into the stream – comments, locations, recommendations, purchases - and this wave of added content (and clutter) will then result in removal of the noisy and unwanted sources, just like any email marketing campaign brings with it a major bunch of unsubscribes.
I doubt we’ll see any social graph shrinkage any time soon, there are so many new profiles generated every second that this will by far offset any of these filtering (mainly by long time users). But we’ll probably start seeing a major wave of edge removal, which was not at all common so far.
Facebook Connect is definitely an excellent move by Facebook to continue dominating and de-facto owning the social graph, with marketing agencies the first to realize and point out the value beyond single-sign-on convenience. With no open alternative that offers the same value, this trend will only accelerate, unless the new OpenID Foundation board members start moving from enabler technologies into active push of equivalent value proposition.
As a followup on Brynn’s review of Delver, I’ve had an interesting exchange with Lachlan Hardy, where Lachlan expressed his disapproval of Delver’s crawling and unifying the social graph (content alone seems ok). My response is in this thread.
The important issue is that socially-connected search requires a comprehensive and unified social graph, which can be quite difficult to achieve. When users conduct their first search, they would expect all of their friends, friends of friends, and their respective content to be pre-indexed, for such a service to be of any use.
Skipping that part makes it impossible to bootstrap, and would be like a web search engine that includes only websites that opted-in to be included in the index, or like a FriendFeed version that shows no public profiles, and if you want to follow someone you must create their consolidated profile yourself. These can be regarded as far more privacy-observing services, but will probably never bootstrap as their real-life counterparts did. It’s all about keeping the balance right.
