Jessica Kent at HealthITAnalytics: “Using machine learning, researchers found that people’s biases about COVID-19 and its treatments are exacerbated when they read tweets from other users, a study published in JMIR showed.
The analysis also revealed that scientific events, like scientific publications, and non-scientific events, like speeches from politicians, equally influence health belief trends on social media.
The rapid spread of COVID-19 has resulted in an explosion of accurate and inaccurate information related to the pandemic – mainly across social media platforms, researchers noted.
“In the pandemic, social media has contributed to much of the information and misinformation and bias of the public’s attitude toward the disease, treatment and policy,” said corresponding study author Yuan Luo, chief Artificial Intelligence officer at the Institute for Augmented Intelligence in Medicine at Northwestern University Feinberg School of Medicine.
“Our study helps people to realize and re-think the personal decisions that they make when facing the pandemic. The study sends an ‘alert’ to the audience that the information they encounter daily might be right or wrong, and guide them to pick the information endorsed by solid scientific evidence. We also wanted to provide useful insight for scientists or healthcare providers, so that they can more effectively broadcast their voice to targeted audiences.”…(More)”.
