Bots, in the context of Twitter, are accounts run by computer programmes that automatically publish and forward content, follow other accounts, leave comments and conduct seemingly "real" activity.
"Right now, you don't know what is coming from a real person and what's coming from a computer, sometimes for malicious, or at least, misleading reasons," said Chengkai Li, from the University of Texas at Arlington (UTA) in the US.
Researchers aim to create computer programmes that distinguish bot from human.
"For example, even if a bot uses high-end artificial intelligence and massive processing power, an extremely simple detection technique may be enough if the bot always posts at the same time of day or has some other trait that makes it easy to distinguish the bot from humans," said Christoph Csallner, associate professor at UTA.
Researchers said that what makes the task especially difficult is that many times fake news' birth has some real facts contained in a report.
"You might find that a bot takes a piece of real and true information, then adds an element that isn't true. So, in the end, you have different levels of fake news," said Mark Tremayne, assistant professor at UTA.
"We will leverage our research expertise in computational fact-checking, static and dynamic code analysis, data mining and security," Li said.
"We will conduct experiments to better understand the interaction between bots and news consumption behaviours and effects," he said.
"By putting together a team of computer scientists and social science scholars, this project, seeks to advance our understanding of fake-news bots and our capability of countering it," he added.