Time is of the essence as a deluge of updates spreads across the internet and social media feeds. Members of the public are eager to find information they can trust.
Time is of the essence as a deluge of updates spreads across the internet and social media feeds. Members of the public are eager to find information they can trust.
False information can lead to harmful consequences. News, social media and government organizations have adopted new strategies in recent years, putting greater emphasis on fact-checking and flagging misleading posts, to provide the important context audiences need.
But how can content creators focus their efforts on areas where the misinformation is likely to do the most public harm? Research from Binghamton University’s School of Management (SOM) offers possible solutions through a proposed machine learning framework, as well as expanded use of blockchain technology.
„We’re most likely to care about fake news if it causes a harm that impacts readers or audiences. If people perceive there’s no harm, they’re more likely to share the misinformation,“ said Thi Tran, assistant professor of management information systems, who led the research. „The harms come from whether audiences act according to claims from the misinformation, or if they refuse the proper action because of it. If we have a systematic way of identifying where misinformation will do the most harm, that will help us know where to focus on mitigation.“
Tran recently presented his research at a conference hosted by SPIE, an international non-profit dedicated to advancing light-based research and technologies.
