Machine Learning and Blockchain Could Counter the Spread of Misinformation
A new research study from Binghamton University, State University of New York, suggests that combining machine learning and blockchain technology could help combat the spread of fake news. The study, led by Thi Tran, assistant professor of management information systems at Binghamton University’s School of Management, aims to provide content creators with tools to identify patterns in misinformation and focus on the most damaging offenders.
Tran’s proposed machine learning systems utilize data and algorithms to recognize indicators of misinformation and improve the detection process. By considering user characteristics and prior experience with fake news, the research team developed a harm index that reflects the potential severity of harm to individuals if exposed to and victimized by misinformation.
The aim of the research is to raise awareness among individuals about patterns of misinformation, encouraging them to verify content before sharing and remain alert to mismatches between headlines and their corresponding content. Tran believes that if people can recognize the harm caused by fake news, they will be more cautious about disseminating it unintentionally.
Tran further explains that the harm caused by fake news lies in whether audiences act upon the misleading claims or refuse to take necessary action. By identifying where misinformation is most likely to cause harm, the proposed machine learning system can help prioritize efforts to mitigate its spread.
The research also explores the user acceptability of using blockchain as a tool to combat fake news. While previous studies have touched on this area, Tran’s research delves deeper into user sentiment towards blockchain systems. The proposed survey aims to assess the willingness of fake news mitigators, such as government organizations, news outlets, and social network administrators, as well as content users, to utilize blockchain systems in various scenarios.
Tran highlights the traceability feature of blockchain as a useful tool to identify and classify sources of misinformation, aiding in the recognition of patterns. By testing different theories, Tran hopes to determine the most effective way to encourage people to utilize blockchain in the fight against misinformation.
The research was presented at a conference hosted by SPIE, the international non-profit organization dedicated to advancing light-based research and technologies. Two papers were presented, one focused on the machine learning-based framework, while the other explored the application of blockchain.
The combination of machine learning and blockchain technology presents a promising approach to combatting the spread of misinformation. As individuals become more aware of the patterns and potential harm caused by fake news, they can take a proactive role in verifying information before sharing it. By harnessing the power of technology, it is possible to mitigate the negative impact of misinformation and foster a more informed society.
