What makes a Tweet Relevant?
That’s the question that both Microsoft and Google are trying to answer since they signed deals with Twitter, Facebook, etc. to have these small “snippets of knowledge” included in their search results.
Couple of days ago, Google has announced that they are starting to push out results from Twitter and Facebook (this hasn’t reached all accounts yet though), so you’d expect that they came out with an approach for measuring the relevance. And I have found the following slide (thanks to ☞ TechCrunch):
In case you cannot read it from the low quality picture, here are the 10 metrics, which are pretty cryptic though,
- Language model (?)
- Tweet quality (?)
- Author quality (?)
- Probability of relevance
- Semantics
- Real-time URL resolution (my comment: probably somehow similar to the old PageRank but reversed: the quality of the tweet is determined by the quality of the links included)
- Query registration (?)
- Query hotness
- Query volume fluctuations
- Topicality (my comment: isn’t this more or less the same with the above Semantics?)
Right now, I cannot read between the lines of this algorithm, but there seems to be 3 dimensions that are considered: the author, the tweet and the included links, the query. I guess we will have to wait a bit longer to find out more about it and to see if it works or not.
