Research shows how content creators reduce the harms of misinformation

Blockchain for fighting fake news: A framework for assessing applicability and acceptance.


The proliferation of misinformation and fake news in the digital age has become a critical societal concern. The rapid spread of false or misleading information can have far-reaching consequences, including social unrest, political polarization, and public health crises. In response to this challenge, researchers have been actively exploring strategies to help content creators mitigate the harms caused by misinformation. This study delves into the various approaches and tools that content creators can adopt to combat the dissemination of false information and promote accurate, reliable content.

Binghamton University‘s School of Management (SOM) research proposes solutions to combat misinformation effectively. With the ever-increasing flood of internet and social media updates, finding trustworthy information becomes crucial. False information can lead to harmful consequences, so content creators have adopted fact-checking and flagging strategies.

However, the research suggests focusing on areas where misinformation poses the most significant public harm. They propose a machine learning framework and the expanded use of blockchain technology as potential solutions to target and mitigate the spread of false information.

Thi Tran, assistant professor of management information systems, who led the research, said, “We’re most likely to care about fake news if it causes harm that impacts readers or audiences. If people perceive no harm, they’re more likely to share the misinformation. The harms come from whether audiences act according to claims from the misinformation or 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 presented his research at an SPIE conference, focusing on two papers. One paper introduced a machine learning-based framework, that can determine the potential harm caused by content to its audience, especially in cases like false COVID-19 treatments versus vaccines.

The framework uses data and algorithms to detect misinformation. It incorporates user characteristics to create a harm index, reflecting the severity of potential harm from exposure to fake news. Another paper discussed the use of blockchain technology in combating misinformation. The proposed machine learning system aims to improve accuracy over time by learning from examples of misinformation and enhancing the detection process.

Tran’s research uses a machine learning system to help identify the most damaging fake news messages if left unchallenged. The system considers individual factors, such as education level and political beliefs, to predict the likelihood of someone becoming a victim of specific misinformation. In addition, the study explores the user acceptability of blockchain technology as a tool to combat misinformation.

Tran proposes surveying fake news mitigators and content users to gauge their willingness to use existing blockchain systems in various scenarios. Blockchain’s traceability feature can help identify and classify sources of misinformation, aiding in pattern recognition. The research aims to educate people about recognizing patterns and being more cautious when sharing information, thus preventing the unintentional spread of misinformation.

The battle against misinformation requires concerted efforts from content creators, researchers, tech companies, and the public. By understanding the scope of misinformation, leveraging fact-checking and verification tools, promoting digital literacy, ensuring algorithmic transparency, and prioritizing credible sources, content creators can play a pivotal role in reducing the harms caused by fake news.

As research continues to uncover new strategies and technologies, content creators must stay vigilant in providing accurate and reliable information to their audiences. Only through collaborative and evidence-based approaches can society effectively counter the spread of misinformation and build a more informed and resilient digital landscape.

Journal Reference:

  1. Thi Tran “Human-machine interactions in the fake news era: an integrated data analytics and behavioral approach”, Proc. SPIE 12542, Disruptive Technologies in Information Sciences VII, 125420O (15 June 2023); DOI: 10.1117/12.2663984
  2. Thi Tran, Oluwafemi Akanfe, et al., Implementations of blockchain applications to fight fake news: an applicability and acceptance investigation framework. SPIE, Disruptive Technologies in Information Sciences. DOI: 10.1117/12.2663953.
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