In the face of an overwhelming surge of updates inundating the internet and social media, the need for reliable information has never been more critical. With the potential for false information to yield harmful consequences, news outlets, social media platforms, and government organizations have intensified efforts in fact-checking and identifying misleading content to provide essential context for their audiences.
Addressing the challenge of pinpointing areas where misinformation is likely to cause the most harm, Binghamton University's School of Management (SOM) has put forth promising solutions through a combined approach involving a proposed machine learning framework and an extended utilization of blockchain technology.
Thi Tran, Assistant Professor of Management Information Systems and lead researcher, emphasizes the significance of identifying areas where misinformation can inflict the most damage: "We're most likely to care about fake news if it causes harm that impacts readers or audiences. If people perceive there's no harm, they're more likely to share the misinformation."
The machine learning-based framework, a branch of artificial intelligence (AI) and computer science, aims to determine the potential harm caused by content and focus on the most egregious offenders. By utilizing data and algorithms to identify indicators of misinformation, the system aims to enhance detection by learning from examples and considering user characteristics.
Tran envisions the system as capable of discerning which messages pose the greatest threat if left unchallenged: "Your educational level or political beliefs, among other things, can play a role in whether you are likely to trust one misinformation message or not, and those factors can be learned by the machine learning system."
The proposed blockchain technology serves as a complementary tool in the fight against fake news, with its traceability feature identifying and categorizing sources of misinformation to aid in pattern recognition. Tran's research goes beyond previous studies by delving into the user acceptability of blockchain systems. A survey involving fake news mitigators and content users aims to gauge willingness to adopt blockchain solutions in various scenarios.
"The research model I've built out allows us to test different theories and then prove which is the best way for us to convince people to use something from blockchain to combat misinformation," Tran explained.
By educating people about recognizing patterns and encouraging vigilance in verifying information before sharing it, Tran hopes to curb the unintentional spread of misinformation. In the ongoing battle against fake news, these innovative solutions offer a promising path toward a more informed and discerning public.
