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Getting consumers to trust quality information is critical

February 7, 2022 | By Rande Price, Research VP – DCN

trusted reputation is crucial for publishers. And, despite the clickbait appeal of fake news, most people value accuracy and truthful content. Research has confirmed time and again that people want to engage more with articles shared by trusted journalists and media outlets, especially on social media.

  • 89% of Americans believe it is “very important” for a news outlet to be accurate and 86% that it is “very important” that they correct their mistakes (Knight Foundation, 2018),
  • 85% say that accuracy is a critical reason for why they trust a news source (The Media Insight Project, 2016).
  • 63% of Americans say they have stopped getting news from an outlet in response to fake news.

However, fake news and low-quality content are still prevalent, amplified, and generating tremendous engagement. Misinformation is not limited by reality and often feeds natural individual biases.

Fighting fake news

The question remains where do publishers place their efforts in the fight against fake news? New research from Alberto Acerbi, Sacha Altay, and Hugo Mercier, Fighting misinformation or fighting for information? explores whether publishers should fight the spread of misinformation or support the trust in reliable sources. Interestingly, the researchers found that it is just as likely that consumers will accept articles and sound bites of fake news reporting as it is for them to reject a piece of accurate news reporting.

The authors developed a model that estimates the effectiveness of increasing the acceptance of reliable news compared to decreasing the acceptance of misinformation. The model includes two main parameters: the share of misinformation compared to the share of reliable information and the tendency for individuals to accept each type of information.

  • Reliable information refers to news shared by sources that, most of the time, report news accurately,
  • Misinformation refers to news shared by sources that regularly share fake and deceptive information.

The model provides a baseline view of the informational environment and offers an approximate index of its quality. Using these broad definitions, the model design includes 5% of misinformation as people’s news diets, with the remaining 95% consisting of information from reliable sources. Importantly the model captures the main elements of an informative environment: the incidence of reliable information compared to misinformation and the tendency to accept each type of information.

The model computes a global information score. The calculation represents the share of accepted pieces of reliable information minus the share of accepted pieces of misinformation.

Simulated exposure

A small sample of individuals simulated in the model were exposed to both reliable and fake news. A larger sample of individuals simulated were exposed only to reliable news. The researchers tested different intervention rates of reducing the acceptance rate of misinformation compared to increasing the acceptance of reliable information.

The researchers analyzed the different interventions rates. The basic simulation illustrates that, even with a 10% incidence of misinformation, improving the acceptance of reliable information by 3% points is more effective than bringing acceptance of misinformation to zero. Therefore, interventions that increase the acceptance of reliable information have a greater effect than interventions on misinformation.

Acerbi, Altay, and Mercier demonstrate the importance understanding the impact of different interventions in the informational landscape. Publishers that place their efforts on increasing the acceptance of reliable information will have a greater effect in the fight against fake news.

These findings do not dispute the many efforts to fight misinformation. However, given publishers’ limited resources, more efforts should be dedicated to increasing trust in reliable sources of information rather than in fighting misinformation.

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