It took me a while to figure out my opinion, but several interesting articles got the stars aligned just right for a split second to make some sense (until some new developments will soon de-align them again ).

Take a deep breath. OK, here it comes:

Google+ is Google’s take on Social.

Yes, I know, who would have thought?…
It’s just that Google’s definition of Social is a bit different.

At Facebook (and really, for most of us), Social is about conversations with people you actually know.
At Google, Social is the new alias for Personalization.

It’s pretty simple: Google’s business model has always meant the more I know about you, the better I can monetize through more targeted ads. At first, it was all about the search engine being where you always start your surfing, and Google was well seated. As traffic to social networks grew, culminating with Facebook overtaking Google on March 2010, it became increasingly clear that a larger portion of our information starts being served to us from social networks. Google was left out.

Why was that so important? Google still had tons of searches, an ever-growing email market share, and successful news aggregation and rss reader, among other assets. That’s quite a lot to know about us, isn’t it?

It turned out that the missing link often was the starting point. You would learn about the new thing, the new trend, the new gadget you want to get, while you were out of Google’s reach. By the time you got into the Google web, you may have already got your mind set on what you want to get and even where, making the Google ads a lot less effective.

The Follow versus Friend model is also a huge issue. It means that G+ is about self-publishing and positioning yourself, and not about conversations. That suits Google very well, and is not just a differentiation from FB. This model drives you to follow based on interest, building an interest graph rather than a social graph, and being a lot more useful to profiling you than your social connections.

That interest graph, in turn, makes sure your first encounter with those things that make you tick is inside the Google web. It also links back well to the fine assets that Google holds today, from your docs to your publishing tools. So when Google News announces those funny badges, and you may have thought “Heh, who would want to put these stinking badges on their profiles…” – think again. Their private nature is just fine for Google. It’s a way to ask you to validate your inferred interests: “So tell us, is that interest of yours in US politics that we have inferred from your news reading a real inherent interest, or was it just a transient interest that will melt away after the election?“. Again – big difference for profiling.

Finally, Google+ is positioned to be a professional network. Focusing on interests and having anyone able to follow you, will keep away the teens and lure the self-proclaimed professionals. In that sense, LinkedIn may have more of a reason for concern, at least as the content network it now tries to be. It’s quite likely that G+ does not even aim to unseat Facebook, only to dry it out of its professional appeal, and leave it with what we started with – party/kids photos and keeping track of what those old friends are up to.

I guess I already know what network I’ll be posting a link to this post to…

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.

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.

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.

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.

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.

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.