Researchers at the Palo Alto Research Center (PARC) are developing new ways to deal with the torrent of information flowing from social media sites like Twitter. They have developed a Twitter "topic browser" that extracts meaning from the posts in a user's timeline. This could help users scan through thousands of tweets quickly, and the underlying technology could also offer novel ways of mining Twitter for information or for creating targeted advertising.
The researchers' idea was to provide a way for users to deal with a large number of Twitter messages quickly. They found that many users wanted to be able to quickly catch up on what's been going on, without having to go through every single tweet in their timeline.
Ed Chi, area manager and principal scientist for the Augmented Social Cognition Research Group at PARC, says that the information coming through Twitter resembles a stream--users will dip into it from time to time, but they don't want to consume it all at once. His group's work is called the "Eddi Project" in reference to the idea of eddies in a stream.
The researchers developed two main ways of filtering Twitter content. The first, presented recently at the ACM Conference on Human Factors in Computing Systems in Atlanta, is a recommendation system that ranks which posts in a Twitter stream a user is likely to find most interesting, based on factors such as the contents of posts as well as his interactions with other Twitter users. The second tool, the Twitter topic browser, summarizes the contents of a user's timeline so that the user can quickly survey what information has come through Twitter without having to read through every post.
From Technology Review
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