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“If you hear the same message from many different sources that you think are independent who are saying the same thing, you’re much more likely to believe it,” says Bruno Gonçalves, a research associate on the project. Repeated messages can also show up as “trending” topics on Twitter, and can even influence Google’s search results. Gonçalves says the researchers are now working to automate the process of identifying suspicious content solely by studying network topology.

The inspiration for the project was a paper published by Panagiotis Takis Metaxas and Eni Mustafaraj of Wellesley College in July 2010. They studied the 2008 special election for a Massachusetts Senate seat between Democrat Martha Coakley and Republican Scott Brown, and found that many Twitter accounts repeated the same negative tweets, apparently in a successful attempt to influence Google’s Realtime search results for either candidate’s name.

In one case, a network of nine Twitter accounts, all created within 13 minutes of one another, sent out 929 messages in about two hours as replies to real account holders in the hopes that these users would retweet the messages. The fake accounts were probably controlled by a script that randomly picked a Twitter user to reply to and a message and a Web link to include. Although Twitter shut the accounts down soon after, the messages still reached 61,732 users.

Bernardo Huberman, who studies social computing at HP Labs in Palo Alto, California, isn’t sure such dirty tricks will accomplish much. In a study that successfully used Twitter activity to predict the popularity of movies, he found that legitimate movie studio Twitter campaigns were largely ineffective compared with honest mass opinion. To truly influence opinion, you have to reach millions of people, not just a few thousand, he says. “Yes, indeed, people are doing this. So what’s new?” he says.

But Menczer thinks Twitter Astroturfing could motivate like-minded readers to get out and vote, discourage political opponents from voting, or influence swing voters. “The cost is almost zero,” he points out. “For the cost of one ad on TV, you could pay 10 people to spend all their time doing this.”

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Credit: Indiana University

Tagged: Computing, Twitter, social networking, politics, election, network analysis, social graph

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