Archive for November, 2009


Socially Augmenting Twitter Profiles with Lists

After adding lists to the hourly press as low-level abstraction, I had some time to reflect upon lists more, and what their value is. A few examples from chatting with Lyn sprung to mind:

Don’t read his bio – the quickest way to see who this guy is, is by looking at the lists he’s on.

and, jokingly,

You should call her up and ask if she thought anyone was missing from her “smart and talented” list.

This started to remind me of my experiences with person tagging at IBM, and I realized that I had already been down this same path. In fact, my earlier (unpublished) variant of the idea was “fringe folders” — almost exactly twitter lists.

What I didn’t like about lists then (and now), is that they don’t combine nicely with each other. Each is a distinct entity, and when there are many of them you have, well, simply many of them. For example, look at Tim O’Reilly who (at the time of this writing) is about to break 4000 lists. Are you going to page through 4000 lists? No one is. Had they been tags, you’d see that 3000 people had tagged him publishing, 2000 had tagged him technology, etc. This could be condensed into a nice, meaningful, overview.

Whether tags or lists are better, the end result is still important because it means that a relatively small number of people can maintain information about a relatively large number of people. What we saw with tags at IBM was that about 3% of the company was tagging 30% of the company, thereby “augmenting” their profiles. This was a socially efficient way of solving a problem. The same will likely be true of twitter lists.

Now, tags can also be used for person search and discovery. On the discovery side, clicking on a tag (say “db2” in IBM) shows you a ranked list of people, sorted by the frequency with which they’d been tagged. Since others were cautious about the way people were tagged, this was a great way to find someone who was knowledgeable about DB2 and receptive to questions about it.

Lists would be a great corpus of data upon which to build twitter user search. In fact, the same feature that makes them imperfect for discovery — their heterogeneity — will make them more valuable for free-text search.


Lists of lists

We’ve added a new feature to the hourly press—the ability to create lists of twitter lists.

The significance of this feature is that we can leverage even more decisions about who’s worth listening to. For example, compose a bunch of lists tracking a breaking news story (like the Fort Hood Shootings last week), and track all of the lists simultaneously.

We’ve also started tracking changes in the social graph, so you can see who’s getting added to these lists. In the case of breaking news, you could use this feature to see who are the new sources being discovered. Twitter doesn’t provide a streaming API for social graph changes, so we resort to polling for updates hourly.

The addition of lists was a technical hurdle, since we’d built in the assumption that the nodes in our social graph are users with twitter_ids stored as integers. We’ve expanded our definition to be more generic, and thus can now incorporate twitter lists, and potentially other kinds of attention focal points.