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Venture Beat published an interview with Google’s Marissa Mayer that ran today written by Doug Sherrets. Andy@Lijit was nice enough to forward it on to me. I’m always interested in hearing what others think about socially influenced search (careful choice of words). Having lived in this world I know some of the more esoteric opportunities and problems of the space.
First, I have to clear the decks with something right out of the gate. The term “Social” has to be the most abused tech buzz word of the last couple years.
Todd’s list of what social isn’t…
- A person, doing something.
- A group of people, who don’t know each other, doing something.
- A group of people, who don’t know each other but behave the same, doing something.
- A group of people, who do know each other, but don’t interact, doing something.
- A group of people, paid by someone, doing something. (test: What search startup is that?)
Quotes from the article with Marissa about Social initiatives at Google:
“One thing we tried…is labeling – have users annotate the search results they see and have those annotations be shared with people on their social network or with people of like mind and interest“
“Another classic thing to try is “other users like you”, where you build implicit social connections between users who are like each other“
“Other users that did that search, also searched for”
“You could take annotations that people have entered in something like Google Coop and broadcast the annotations.”
You see what is happening here don’t you? What derails ideas about social search are very simple. The Internet world grew up with a one box, take a pill, mentality. If we can’t search the entire world’s data in one box and have that box know what we mean, it’s a non-starter because of what we have come to expect.
Yet, social behavior is just the opposite. Social behavior is about the people we “know”. It’s important to “know” people in order to validate the result set they help deliver to you. We don’t “know” everyone and that contradicts the “one box” expectation of social based search. It also contradicts the “best answer” expectation. No matter how grand the plan is for social search you need to “cross the chasm” of who you and your network know, and who you and your network does not know.
For social search to work in a global, one box world, it cannot be completely a social model. What does work is using a social network of people you “know and interact with” to find a “local expert” within a known network. That “local expert” will likely have pointers to high quality data produced by “global experts”.
The system is not perfect. But it does work quite nicely in practice within the world of general knowledge and day-to-day problem solving, around YOU. Where the system is does not work as well are in situations where the local network, as whole, has little basic knowledge of the item or concept being searched. Interestingly, these are the situations where more traditional information stores like Wikipedia work exceedingly well. This is why I feel quite satisfied when I look up Nuclear Reactor in Wikipedia, but a person in the Nuclear Power space would look to his network to find more detailed information.
The graphic above is really what we want to achieve at Lijit. Though our Search Wijit we facilitate and explore the connections, discussions, and searches of connected “real” social networks. These people interact, get to know each other, have a proxy (the blog) for the metadata that exists in real world physical relationships. In other words they do more than simply throw food at each other. When the network – of networks – hits a critical mass we should have global pointers needed to cross the social chasm – in one box.
Scoble has a great couple of podcasts today on Social Graph based search. He talks about how new social based search plays are resistant to SEO (Search Engine Optimization) and are eventually going to kick Googles ass.
This is exactly the basis of what Lijit was founded on. The idea of social trust being the major driver in judging the value of content is spot on.
Scoble talks about how Mahalo is a social graph based search because they have content editors that are part of their social graph. I think the example is a little broken in the Mahalo case in that the graph is not really naturally occurring. In other words the graph as selected based on social popularity, who wants the job, etc. perhaps not actual expertise in a specific domain. He also suggests Facebook is in a great place to capitalize on their large social graph to revolutionize search. I agree, however Facebook is still a walled garden of content. If Facebook would extend their social reach (and content reach) beyond their walls they would be in a great position.
Lijit is using the naturally occurring networks that already exist out on the web to create powerful search from the ground up. We don’t hire content editors and we don’t force editors (publishers) into any specific social network. Lijit uses the networks you have to build the world’s most powerful foundation for search.
Great post Robert, we agree.