This is also why Color’s launch was received with such mixed reviews. They are trying to use location as the implicit social graph, but there is no real interest. Even if there are several people at the same location, the location may denote different purposes. As an example, if I am at a restaurant I probably do not want the interruption that would come with a location based graph. However, if I am visiting a tourist attraction I may welcome the location-based interaction, mainly because there is implicit interest in the location.

Fred Wilson has a very good description of how he was introduced to implicit graphs:

My first experience with this sort of implicit social graph came almost six years ago via my musical neighbors graph at last.fm. I don’t think I actually know any of these people in real life, but they are the last.fm users who have the closest taste to mine in music, right now. That right now is important because my musical neighbors graph looked differently last year and will look differently next year.

Obviously, people’s musical tastes change over the years, so a static graph is not entirely useful. The “musical neighbors” concept and Pandora’s music genome concept allow for discovery because they are using similar interests to create the implicit graph. A person’s friends may not have the same musical tastes and thus would actually clutter the listening experience with music the listener is not interested in.

In addition to the creation of implicit graphs, sometimes there needs to be a conversion from the implicit to the explicit graph. Colin Walker talks about this in reference to sporting events and other interest-based interactions:

Repeated interactions within implicit graphs can lead to a bleed from the implicit to explicit – once you get to know them some of those from implicit graph become ‘friends’ and, after a while, can be invited over in to the explicit graph.

This bleeding complicates the structures of explicit graphs because these new “friends” are not initially the same type of friends as those people you have known for years. Then there are some people in your explicit social graphs that you lose contact with. Even though they could have been friends previously, differing interests and the effects of time can change their relationship to you. This is where the concepts behind Color become interesting. Obviously, there needs to be some flexibility or “elasticity” in your social graphs, regardless of whether the graph is explicit or implicit. Color CEO Bill Nguyen had an interesting comment about this in a ReadWriteWeb article:

In the world of Facebook, once someone is your friend, they’re your friend until you return and re-evaluate that relationship, regardless of whether or not you’ve ever spoken to them again. In reality, the relationship could have fizzled long ago, yet it’s still a bond as good as any. With Color’s “elastic” social graph, these ties can fade and disappear. Color’s ability to accurately determine location and user proximity is what makes this sort of social graph – an implied, impermanent and elastic social graph – even possible.

As I previously stated, I do not agree with the importance of location in this quote, but the general concept is important. Location and time can both be an attribute of the implicit social graph, as can be seen with the SXSW conference. Just because you are in Austin does not mean that you share the social graph with a bunch of people. However, if you happen to be near specific locations in Austin during the same time as the SXSW conference and you have previously shown interest in web and technology startups, then you would be part of the same implicit social graph. Without the interest part of the equation, you could become part of the implicit graph purely by coincidence, maybe you work or live in Austin.

Om Malik has an excellent post this morning that really hits the same points, but talks about them differently. He mentions “happiness” and “utility”:

One of the reasons Instagr.am works is because it has that “happiness” attached to it. When I see my friend’s baby boy, it brings me joy. I see Mathew Ingram at an ice hockey game; it makes me warms my heart to see him enjoying time with his family. I reward Instagr.am with my attention because it makes me happy. That is its utility.

His examples and Fred Wilson’s examples are excellent reasons why some social applications really work well and others don’t get traction.  Implicit social graphs are really driven by interests where time and location can be attributes of that interest but they are not the primary definition of that interest.

Originally published on Regular Geek

A recent post on the Facebook Developer blog discusses just that. "As part of Operation Developer Love, we are are continuing to update our documentation," said Facebook’s Ankur Pansari. "Recently, I was talking with some developers in New York, and they were surprised to learn that they could publish updates to people who have liked their Open Graph Pages."

"You can publish stories to people who like your Open Graph Page the same way you write a Facebook post from your own wall. The stories appear in the News Feeds of people who have clicked the Like button on the Open Graph Page," he added. "You can also publish using our API. If you associate your Open Graph Page with a Facebook app using the fb:app_id meta tag, you can publish updates to the users who have liked your pages via the Graph API."

A tip of the hat goes to Josh Constine at InsideFacebook for pointing this out, as well as raising a good point that publishers should consider: "For instance, retailer Urban Outfitters has Like buttons on every product in their website’s ecommerce store. It sells a wide variety of products, from clothing to bikes. If the Urban Outfitters Facebook Page posted an updated about a new line of bikes it was carrying, only a small part of their audience would find it interesting, while a large portion of their audiences would find the update irrelevant or even spammy, leading them to click the Unlike button."

"Instead, Urban Outfitters could publish the update about bikes to only those users who’ve clicked Like buttons on their bikes," he adds. "By sending product-specific updates to those who Like that type of product, Urban Outfitters can send higher relevancy updates more frequently but to less people, increasing click through rates and driving more traffic to their website without spamming all 600,000 fans of the Facebook Page."

Basically, this has the potential to be a very powerful tool for anyone using "like" buttons on their sites, but like any other powerful tool, handle with care.

SES New York is here again, and WebProNews is there to bring you reports and videos from the Big Apple. Enjoy our coverage this week.

Calacanis’ presentation was less about snake-oil this time, and more about legitimizing white-hat SEO while promoting a new social graph he is adding to Mahalo. Calacanis assured the crowd that he meant no offense to the SEO industry in his last presentation, and admitted that his impression was more in line with black-hat SEO or, as he put it, "black magic" SEO, which is more about gaming search engines than legitimate site architecture.

"In some ways," he said, "I am an SEO. I’m a white hat SEO," so long as that means building clean sites.

Calacanis said Mahalo was built on a similar concept as DMOZ or Yahoo Directory, both of which he says failed in terms of search because the directories were "neglected." Calacanis believes Mahalo will not suffer the same fate because the Mahalo Greenhouse Most Wanted page, which distributes the work of building search results among 400 at-home workers.

He said Most Wanted trails only Wikipedia and About.com.

The problem remaining, he said, was keeping the content up-to-date, a problem he addresses by launching Mahalo Social, a social graph that allows users to recommend links and updates in order to build a trust score.

Then there’s the problem of user bias. Calacanis claims that, unlike Google or Yahoo, ranking in the results is up for discussion and review in public view.

The system is based upon machines, experts, social influences like friends, and the fabled wisdom of crowds. A search for Macbook Air, for example would bring up blogs, reviews, and sites like Stumble Upon, all of which are integrated into the social graph, which includes also Del.icio.us, blog comments, Wikipedia, and Digg.

Apparently not Netscape, though.

Using My Mahalo, a user can see at the top of search what friends are recommending in terms of movies, books, services, or products. No friends? No problem. The most "trusted" sources will be posted first with user-ratings posted along the right and bottom.

The idea behind this is that social information is more valuable in search than it is in the original destination like at MySpace or Facebook. The concept is more closely related to the semantic web, which relies more on human categorization, but Calacanis says an algorithm, which has yet to be developed, is important to the further development of the concept.

Part of this semantic integration would include the incorporation of information outside of Mahalo. For example, social information from GoodReads, a site for book lovers, or Netflix for movies, would appear in a networked search result. This of course, in light of recent Facebook privacy fiascos, would be on an opt-in basis.

Mac clients have a new version of the Plaxo application, which brings their Pulse feature to the Address Book. Pulse hooks up to what people call the ‘social graph’, essentially the social networking people do through a variety of services like Twitter, Digg, and other sites.

Plaxo users will want to use some care in setting up Plaxo, either in Mac Address Book or in Microsoft Outlook. Pulse can very effectively share one’s social activity with other contacts in Plaxo. While that may be the great promise of the social graph, there might be things people would rather not have charted with all of their contacts.

Once in place, Pulse for Mac Address Book provides a single point of contact for the various social updates other Plaxo connections perform. But wasn’t the whole point of the modern Internet, and even Plaxo, to free people from a fixed software client?