Now that Microsoft and Google are going to search Twitter, how to make that useful? Social search is clearly part of the answer – filtering results based on social proximity, based on friend/follow lists. There’s another piece that is missing – the context of the conversation. In Twitter, conversations are represented implicitly by a series of replies between users. Twitter itself does not show that explicitly, though there are clients that do so.

The thing is, in Twitter, each message is very short, and often depends for context on a poster’s previous tweet, and on her replies to other correspondents. So in order to deliver meaningful results, it would be useful to algorithmically reconstitute the conversation.

The border of a conversation is fuzzy. In the recent conversation between Howard Rheingold and his Twitter followers on multi-tasking, there were a series of back and forth exchanges, that interspersed a bit with other topics. An algorithm would approximate the cutoff points where the topic changes, and the conversation ends.

Then, the search result could be shown in the context of the conversation, and make more sense.

The spark for this post is a conversation between me, Thomas Vander Wal and Alan Lepofsky on Twitter.