For social search, similarity could trump friendship

There's a difference between people you know and the people you're like.

Just because I friend or follow someone doesn’t mean we’re alike. We might be colleagues or classmates. Maybe we’re both fans of a baseball team or a certain twisty TV show. That’s the extent of our overlap.

Altimeter Group founder Charlene Li (@charleneli) touched on the difference between people you know and people you’re like during our interview at Web 2.0 Summit. Here’s our exchange:

Will social search and algorithmic search eventually combine?

Charlene Li: I think social search has been bandied around for a long time as an additional signal to pure algorithmic search. Social was just another input into the algorithm in the same way that Page Rank or word frequency might be …

You have two types of social graphs in there: people you know and also people like you. That’s the part around personalized search that’s also in semantic search, because language is unique to each person.

During our chat, Li said the partnership between Facebook and Bing is a step toward a unified social-algorithmic engine because Bing is extracting patterns from Facebook data. It’s not blindly tossing queries into your Facebook network.

After speaking with Li, it occurred to me that the current state of social search is reminiscent of those pre-Google days when results seemed arbitrary. I’ve encountered that old “ask and pray” feeling myself whenever I pose questions to my networks. Sometimes I receive useful information — stuff I’d never get from a strict search engine — but there’s no rhyme or reason to that process. Occasionally, there’s no response at all.

Social search built around similarity — the “like” rather than the “know” — could improve its reliability. To increase the chances and relevance of similarity, social engines need to also expand the boundaries of “social proximity” to include friends of friends and others adjacent to your social graph. This cocktail of similarity and expansion could yield the Page-Rankian shift that transforms social search from an occasional option to a reliable resource.

If you’re interested, the full interview with Li is included in the following video (the part about social search starts at 1:45):

Note: Portions of this post were edited after initial publication. Changes were made for clarity; it was hard to determine which comments were associated with Charlene Li and which were made by me. My apologies for any confusion. — Mac.


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