Predictors of the authenticity of Internet health rumours

Abstract

Background: The Internet is becoming an important source of health information; however, unverified health rumours may be included in health-related search results. There is a critical need to provide health information seekers with methods that are specifically geared towards the identification of the authenticity of health rumours. Methods: Using 453 health rumours collected from a definitive online reference of rumours in China, this study investigates which features contribute to distinguishing between true and false rumours with a logistic regression model. Results: There are measurable differences between true and false health rumours on the Internet. The lengths of rumour headlines and statements and the presence of pictures are negatively correlated to the probability that a rumour is true, whereas a rumour is more likely to be true if it contains elements such as numbers, source cues and hyperlinks. Finally, dread health rumours are more likely to be true than wish ones. Conclusions: Despite the growing number of studies on rumours, the identification of the authenticity of rumours has received little attention. This study proposes some rules of thumb to help online users ascertain rumour veracity and make decisions.