The increase in so-called “fake news” has created great concern in the U.S. news media. At present social media and other digital platforms play a significant role in the dissemination of news-making U.S. news consumers vulnerable to viewing potential misinformation and unverified information presented as if accurate.
Many digital outlets like Facebook and Twitter use opinion or behavior-based metrics such as user ratings to suggest stories to their users. But artificial users or bots have the ability to manipulate the metrics and so both reliable and unreliable news stories are served to the users of the digital platforms.
Recent research from Gallup and Knight Foundation tried to find out how the use of opinion or behavior-based metrics influenced the level of trust in the media. The study used a custom-built news aggregation platform that showed 11,695 study participants up-to-date news stories from seven prominent news outlets. The participants were asked to rate their level of trust in every news article they read using a 5-point Likert scale.
Participants who viewed either the community average trust rating or the “people like you” average tended to be less trusting of the articles they read, compared with the groups who viewed their own past behavior or no past ratings. Participants who saw their own historical average trust rating generally remained consistent in how they rated news outlets before versus during the experiment.
Gallup and Knight Foundation acknowledge support for this research from the Ford Foundation, the Bill & Melinda Gates Foundation, and the Open Society Foundations.