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IU Researchers Develop Tool To Identify Twitter Bots

BotOrNot analyzes social media data to determine if a Twitter account is manned by a human or a bot.

If you’ve ever used a Twitter account, chances are you’ve probably encountered a tweet or a message that seemed like it wasn’t written by a human.

More and more companies are using automated software applications known as “bots.” Bots are automated software applications designed to generate automated content on social media on Twitter.

A team of complex networks researchers at Indiana University have developed BotOrNot, a tool to help determine if a Twitter account is manned by a human or a bot.

Clayton Davis is a PhD student at Indiana University in the school of Informatics and Computing and part of the BotOrNot project team.  He says BotOrNot is the first social media analysis tool of its kind.

“Accounts that you might be following, or might be paying attention to on Twitter, might be bots – and you might not think about it or realize it,” Davis says. “And it’s not bad or anything, but up until now, except for just tweeting them and asking them – which if it’s a bot, it may not respond to you, there hasn’t really been a way to figure out if someone is human or not.”

No one knows how many bots are out there, and most are totally benign. But the researchers say bots could be dangerous for democracy, cause panic during an emergency, affect the stock market, facilitate cybercrime and hinder advancement of public policy.

BotOrNot analyzes over one thousand features from a user’s Twitter account to calculate the likelihood that the account is a bot.  Anyone can use the BotOrNot website.

The project is funded by The National Science Foundation and the U.S. military are funding the research after recognizing that increased information flow through social media, combined with mobile technology, is making it easier to spread information – or misinformation.

BotOrNot is part of the Truthy project, an umbrella of different projects analyzing and visualizing social media data.

“We’d really like to be able to help the government and interested parties detect, in sort of real time, misinformation campaigns that are going on,” Davis says.

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