After an election year marked by heated exchanges and the distribution of fake news, Twitter bots earned a bad reputation—but not all bots are bad, suggests a new study co-authored by Emilio Ferrara, a USC Information Sciences Institute computer scientist and a research assistant professor in the department of computer science at the USC Viterbi School of Engineering.
In a large-scale experiment designed to analyze the spread of information on social networks, Ferrara and a team from the Technical University of Denmark deployed a network of algorithm-driven Twitter accounts, or social bots, programmed to spread positive messages on Twitter.
“We found that bots can be used to run interventions on social media that trigger or foster good behaviors,” says Ferrara, whose previous research focused on the proliferation of bots in the election campaign.
But it also revealed another intriguing pattern: information is much more likely to become viral when people are exposed to the same piece of information multiple times through multiple sources.
“This milestone shatters a long-held belief that ideas spread like an infectious disease, or contagion, with each exposure resulting in the same probability of infection,” says Ferrara.
Note: The research discussed in the article above is linked below: “Evidence of Complex Contagion of Information in Social Media: An Experiment Using Twitter Bots” (via PLOS One)