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(adapted from my answer on Quora)
With the mass adoption of social networks, I’ve been thinking about the use cases that benefit from analyses of multiple degrees of separation
For sake of clarification, I consider the “social graph” to be one where the nodes are people as opposed to documents (eg, pages). The connection between the nodes do not have to be friends or explicit. They can be links between people due to a common interest (eg, people who follow the same topic on Quora) or implicit connections like the ones Color Labs is trying to create.
The main business cases will be one where you can reasonably infer an answer from related data points.
I think the primary use of the social graph is recommendation. I can’t count how many start-ups promise to suggest to me what films, restaurants, hotels, books, clothes, music and other stuff my friends like.
I think these startups are currently, overly dependent on explicit connections (“friends”). An emerging business case–an important one in my view–is reputation. Klout and PeerIndex are the two players I know in this space.
Brainstorming, other business cases might include: management of contagious diseases; polling; political repression.
(adapted from my answer in Quora)
I see them fulfilling uses cases such as:
– I search for “Rush” to find what Twitterers are the most authoritative about this awesome Canadian band;
– Rush management wants to promote their new tour and need to find who are the super fans to spread the word.
When people talk about PageRank; about figuring out that Page A is important because loads of other pages are linked to it (I know other signals are considered); they take for granted that Google knows what topic Page A covers. So when you search for “Rush” you get a result of the most authoritative page about the band.
In the page-centric web world, where the node is the page, we’ve all been trained to write super topic-focussed, use key words and provide meta-tags. Even if the page refreshes a bit, which it should to preserve it’s SEO ranking, we will keep it on topic.
When it comes to the people-centric world, where the node can be a Twitter account (usually a person) we are a mess. It’s easy to determine that an account has more followers (and other signals of popularity) but it’s nigh impossible, so far, to figure out why. The regular account will not only tweet about a topic they are authoritative but also about sports results, good movies, funny YouTube clips and many other subject matters that interest them. The same applies to Facebook updates, Google+ postings, etc.
PeerIndex is trying to figure what a Twitter account is authoritative about by analysing the content of their tweets (and other social media content). In my personal experience it doesn’t work (yet)–what they think of me is completely incoherent.
Klout appears to have opted for a crowd sourced solution with +K. They identify what an account might be about but then let loyal registered users (those that login at least once a day) to vote up their best guesses.
Prediction: I think these two players will be snapped up by one of the big boys: Twitter, Microsoft, Google or LinkedIn within two years.