Twindex won’t clean your windows but it will leave you trying to figure out more words to combine with Twitter. TWINSANE!
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Twindex won’t clean your windows but it will leave you trying to figure out more words to combine with Twitter. TWINSANE!
In the roll up to the 2012 elections, Twitter has announced the Twitter Political Index, or as the New York Times calls it, “Twindex.” The index is designed to show Twitter users’ sentiment towards 2012 presidential candidates. From the Twitter blog announcement:
Each day, the Index evaluates and weighs the sentiment of Tweets mentioning Obama or Romney relative to the more than 400 million Tweets sent on all other topics. For example, a score of 73 for a candidate indicates that Tweets containing their name or account name are on average more positive than 73 percent of all Tweets.
The index, which Twitter says is meant to add to, not replace other political polls, will be updated each day at 8:00 p.m. Eastern. Data is being culled, filtered, and sifted by Topsy, a company that specializes in online search and analytics. The Times spoke with Adam Sharp, Twitter’s head of government, news, and social innovation:
Mr. Sharp said the index had a database of thousand of words to understand if these Twitter messages were for or against a candidate. As these messages are being shared by millions of people on Twitter, the software also takes into account colloquialisms.
Mr. Sharp noted that “bad,” for instance, could mean bad, or it be slang for good. He said that Topsy could differentiate between these words in a sentence and if they are positive or negative.
Hear that? You can call the Obama campaign “groovy” or tweet “Aces!” to Romney, and the database will totally get it.
The big question I have, however, is that now this information is public and we know there are just shy of 70 gajillion bots running wild on Twitter, who’s going to stop people from trying to game the system? Not necessarily one of the candidates, but ANYbody could just start sending out truckloads of automated positive/negative tweets about a candidate and shift the numbers.
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