I and my
friends at Institute are Twitter fans. We are inspired by novel opportunities
that amazing new medium - Twittersphere - naturally provides.
Today a lot
of people talk about real-time search upon Twitter.
Most of them understand real time search as a new possibility of getting
breaking news quickly. Bright examples are January plain crash at Hudson and Mumbai
terrorists attack.
News about these events outrun CNN, and was received straight from the tin. Of course, that
is a wonderful thing about Twitter, but we can get even more if
consider real time search widely.
If something is happening in the world it makes buzz on Twitter. The buzz especially intensified due to Twitter-native retweet feature. So, events that happen in the world coincide with activity bursts on Twitter (I mean something more global than @mariagrineva :Just bought new mega cool gloves), and that not only true for events as big as terrorists attack, but also, for example, Damon Albarn presenting his new single on British radio. This feature of Twitter media should be used not only to capture breaking news, but to sort out important events related to the search query that took place any time ago.
Here is a
snapshot of a TweetSieve that we are going to present at SIGIR conference this
year. The user types in her query. The system then shows the
period of events occurring for the query subject and outputs tweets that best describe each of the events. Snapshot
shows a case for “Semantic search” as a sample query.
Basically,
TweetSieve does the following : (1) it identifies activity bursts in
Twittersphere related the user query and (2) selects tweets that best describe
news events using algorithm similar to this one. More details are in paper (Sifting Micro-blogging Stream for
Events of User Interest), I will make it public after the conference.
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