Technological factor, barrier 5 of 7

Misinformation

Vosoughi, Roy, and Aral (2018) studied about 126,000 verified true and false news stories shared on Twitter from 2006 to 2017.

Evidence

Reach. False news spread significantly farther, faster, deeper, and more broadly than true news in every category.
Topic. The effect was strongest for political news.
Novelty. False news was more novel, which may explain why people shared it.
Human sharing. Automated accounts spread true and false news at the same rate, so the difference came from human sharing.

Why it matters: When falsehoods spread faster than facts, public decisions on health, science, and policy suffer. This reinforces the identity-protective thinking described in the cultural factor.

Proposed and experimental methods

Methods that are proposed, under trial, approved in some places, or tried and then failed. Each shows a stage label and an evidence rating. A stage label shows how far a method has progressed, not whether it works. The stage labels are explained on the technological factor page.

Fact-checker warning labels (Large trial, B). Platforms attach a warning from a professional fact-checker to false posts. Across 21 experiments with 14,133 participants, labels reduced belief in false headlines by 27.6% and sharing by 24.7%, and still reduced belief by 12.9% and sharing by 16.7% among those most distrusting of fact-checkers (Martel and Rand, 2024). The experiments were online surveys rather than live platforms.
Short media literacy tips (Large trial, B). In preregistered survey experiments modeled on Facebook's tips for spotting false news, the tips improved discernment between mainstream and false headlines by 26.5% in a nationally representative U.S. sample and 17.5% in a highly educated online sample in India, the U.S. effect was still measurable several weeks later, and there was no effect in a largely rural area of northern India with low social media use (Guess et al., 2020). A correction to the article was published in 2023.
Platform regulation through the EU Digital Services Act (Approved but not scaled, C). The regulation, adopted on October 19, 2022 (European Parliament and Council, 2022), requires platforms with over 45 million monthly EU users to analyze and reduce systemic risks, including to electoral processes and public health, and allows fines of up to 6% of global annual turnover. The Commission designated the first 17 very large platforms and 2 search engines on April 25, 2023 (European Commission, n.d.). No study has yet measured its effect on misinformation.
Cross-references. Accuracy prompts and prebunking games and videos, with their replication disputes, are covered in "Cognitive dissonance and motivated reasoning" in the psychological factors, together with Community Notes and feed reranking.
Reversed: third-party fact-checking at Meta in the U.S. (Failed or reversed, B). Meta said in January 2025 that it would replace U.S. third-party fact-checking with a crowd-sourced notes system (Associated Press, 2025), even though the warning labels that fact-checks produce had reduced belief in and sharing of false posts in experiments (see the first entry in "Misinformation" in the technological factors).

Sources cited on this page

Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146-1151. DOI B Moderate
Guess, A. M., Lerner, M., Lyons, B., Montgomery, J. M., Nyhan, B., Reifler, J., et al. (2020). A digital media literacy intervention increases discernment between mainstream and false news in the United States and India. Proceedings of the National Academy of Sciences, 117(27), 15536-15545. link B Moderate
Martel, C., & Rand, D. G. (2024). Fact-checker warning labels are effective even for those who distrust fact-checkers. Nature Human Behaviour, 8(10), 1957-1967. link B Moderate

Every source for this factor is listed on the technological factor page.