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Will Facebook Join OpenSocial?

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Will Facebook Join OpenSocial? R/WW Readers Split 50/50!

Intriguing question: who will choose to join the OpenSocial opportunity Max blogged about?  Traditional wisdom suggests that only the losers benefit from standardization, and that the winners will try hard to stay away from it.  (And, if they do join it, to embrace and destroy the standard, but that’s another story.) 

It’s easy to explain the advantage to everyone else of having Facebook join the party.  What are the advantages to Facebook?  Social networking sites should be a vortex, with people motivated to join and stay on the sites with the most other users.  Making it easy for people to migrate their information would reduce the stickiness.  If this analysis is correct, the only way for the rest of the world to win would be for the community of “everyone else” to be larger than the community Facebook can attract itself.  It would be interesting to analyze the distributions of membership on social network sites that lead to success for openness versus those that predict that proprietary is the way to win.

John

ScribeFire

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ScribeFire is a cool tool that makes it easy to create a blog entry in your favorite blog tool.  Just install the plugin, add your favorite blogs, and you’re one click from publishing to the blogs.  A very nice example of how a tool can lower the barrier to entry just enough to let you blog about things that you might otherwise just smile at :).

Even more fun: the current developer is Chris Finke, a very talented former Chipmarker!

John

ScribeFire: Fire up your blogging

Community Policies Fighting Communities

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Two interesting examples of businesses fighting their communities came up this morning in my reading.

Example 1.  Amazon is selling Bill Clinton’s new book, Giving.  They also deleted about 20 reviews from the product page.  Presumably, these reviews were mostly low, mostly given by folks who don’t agree with Bill’s politics.  Amazon, however, is in the business of selling books, and low reviews posted by people who are clearly not the target demographic do not help them make money.  Thus, the reviews go away, and people get angry.  Would better moderation interfaces, or different moderation policies affect the need for this type of "censorship"?

Example 2.  Yahoo! Answers developers post a blog entry that basically says: stop using Yahoo Answers as a social space, and start asking intelligent questions. There are two prominent sub-communities of YA that are clearly not about Q&A discourse.  There is the polls community, where people ask questions like "which pair of jeans should I wear tonight", and the politics community that focuses on flame wars.  Why doesn’t Yahoo! seem to care about these thriving sub-communities?  Well, perhaps they don’t promote Yahoo’s vision of social search, where a huge Q&A database helps Yahoo reclaim the #1 search engine slot.

These examples illustrate to me the challenges that businesses face in leveraging users’ work as part of their core business.

Max 

So should I buy a Mac?

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I’ve been thinking about buying a new computer, and after some Mac-koolaid-dispensation from Barry Smyth, I started to consider getting a Mac. Here’s an article that claims Macs aren’t just better but cheaper than PCs, too. So, should I buy a Mac?

OpenSocial: impact on recommenders

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Google and several partners recently launched OpenSocial, an open API for accessing social network information. If you haven’t read about this yet, check out the NY Times article for a primer.

Social networks aren’t the only domain where sharing information between sites is a much-requested feature. Indeed, we’ve all invested significant time in building (perhaps redundant) databases of our preferences in recommendation systems such as Netflix, Amazon, and MovieLens. Wouldn’t it be nice if those ratings would be portable? Then I could sign up for Netflix, and instantly bring my hundreds of movie ratings with me.

Of course, there are a number of issues with ratings portability, such as:

  • What is an entity, and how is it uniquely identified?  (e.g. Is the entire first season of the TV show The Wire a single "tv show entity", or several?)  How is an entity’s category/type determined?
  • How do I communicate my preferences for an entity to the system? Do I use a single 5 star scale, a set of yes/no questions, open text, or something else?
  • Why would any large company wish to share it’s ratings database? (Yes, Netflix and MovieLens have published ratings data sets, but those ratings have been anonymized)

While these are significant issues, I wonder if an open ratings API (built on a platform such as OpenSocial) would clear the path to more ubiquitous recommendations. We could allow MovieLens users to publish their ratings to OpenSocial. Myspace developers could then create a variety of social- or algorithm-driven recommendation systems based on this new source of data. If we were running MovieLens to make money, we’d probably try to build these apps ourselves, and sneak in viral features to bring more new users back to our site.

In the short-run, there are other nice benefits of OpenSocial for small-ish recommendation sites such as MovieLens. For example, could we do away with our "buddy" feature, and just allow users to import their social network from Myspace?

Max

(Note: some newer recommendation companies like Flixter and iLike are OpenSocial "launch partners").