In a recent post I defined the idea of Twitter ListMates as IDs that are frequently grouped together on the same twitter lists. The listmates for some starting ID give an interesting perspective on how that ID is perceived by others and are in some sense similar to it.
If the starting 'seed' ID is highly characteristic of some particular domain then the highest ranking listmates will also be characteristic of that domain. As a concrete example, let's start from infosthetics, the twitter account for one of the central websites in the area of data visualization. The top ranking listmates are: flowingdata, datavis, and infobeautiful which are all very important voices in the domain.
If we start with all four of these IDs, find the lists they are on, and see who else appears on the same lists the most often we can get an excellent quality list of twitter IDs for the field of data visualization. By starting with a small set of IDs rather than just one we introduce less bias into the result. Another technique that can be used to improve quality is to only use twitter lists whose name matches the domain as well - for example include the members of a list called 'datavis' but not of one called 'friends' when determining the listmates.
I have used this technique to define a number of twitter lists for various domains and saved them under the twitter ID Top100in. The lists defined so far are: