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Tuesday, 11th May 2010

Carnegie Mellon University: Study Finds Opinions on Twitter Similar to Those in Polls

From the Pittsburgh Business Times:

Sifting through a billion tweets sent between 2008 and 2009 researchers at Carnegie Mellon University say they may have found a new way to measure public sentiment that could be just as accurate as traditional polling methods.

Using text analysis researchers looked for messages on Twitter, a microblogging service, about the economy or politics and then looked for words that indicated a positive or negative view. Results were then compared with the Index of Consumer Sentiment fro Reuters/University of Michigan Surveys; the Gallup Economic Confidence Index; the Gallup daily tracking of presidential job approval; and polls from pollster.com.

[Access the Full Text Paper] From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series (PDF)

by: Brendan O'Connor, Ramnath Balasubramanyan, Bryan R. Routledge, and Noah A. Smith

The paper is scheduled to be presented on May 25th in Washington D.C. at the Association for the Advancement of Artificial Intelligence’s International Conference on Weblogs and Social Media. Here's a list of the accepted conference papers. We will try to get our hands on the papers we think will be of most interest to you and then link to them on ResourceShelf.

See Also: Twitter a Decent Stand-In for Public Opinion Polls (via Ars Technica)


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