Social Bots, or accounts from non-genuine people, are posted all over social media. They infiltrate popular topics and serious ones like the Covid-19 pandemic. These bots are not like obvious robocalls or spam emails. They are designed to be human-like and interact with real social media users without their awareness. In fact, recent studies show that social media users find them mostly indistinguishable from real humans.
Now a study by Stony Brook University and University of Pennsylvania researchers published in Findings of the Association for Computational Linguistics (ACL) attempts to look at how human these social spambots really are by estimating 17 human attributes of the bot and implementing state-of-the-art machine learning and natural language processing. The study findings shed light on how bots behave on social media platforms and interact with genuine accounts, as well as the capabilities of current bot-generation technologies.
“This research gives us insight into how bots are able to engage with these platforms undetected,” explains lead author Salvatore Giorgi, a Visiting Scholar at Stony Brook University and a PhD student in the Department of Computer and Information Science (CIS) at the University of Pennsylvania’s School of Engineering and Applied Sciences. “If a Twitter user thinks an account is human, then they may be more likely to engage with that account. Depending on the bot’s intent, the end result of this interaction could be innocuous, but it could also lead to engaging with potentially dangerous misinformation.”