Content characteristics predict the putative authenticity of COVID-19 rumors - Zhao, Jingyi; Fu, Cun; Kang, Xin (Frontiers in Public Health, 2022)
Rumors regarding COVID-19 have been prevalent on the Internet and negatively influence the control of the pandemic. Using 1,296 COVID-19 rumors collected from an online platform (piyao.org.cn) in China, this study probes into content characteristics that may contribute to the distinction between "true" and "false" COVID-19 rumors. Our findings show measurable differences in the content characteristics between true and false COVID-19 rumors. Using a logistic regression model, we found that the length of a rumor's headline is negatively related to the probability of its being true (OR = 0.37, 95% CI [0.30, 0.44]). In contrast, the length of a rumor’s statement is positively related to this probability (OR = 1.11, 95% CI [1.09, 1.13]). In addition, we found that a rumor is more likely to be true if it contains concrete places (OR = 20.83, 95% CI [9.60, 48.98]) and specifies the date or time of events (OR = 22.31, 95% CI [9.63, 57.92]). It is also likely to be true if it does not entail positive or negative emotions (OR = 0.15, 95% CI [0.08, 0.29]) and does not call for actions (OR = 0.06, 95% CI [0.02, 0.12]). By contrast, the presence of source cues of the information (OR = 0.64, 95% CI [0.31, 1.28]) and the use of visuals together with text (OR = 1.41, 95% CI [0.53, 3.73]) are not significantly related to this probability. These findings provided some clues for identifying COVID-19 rumors using the content characteristics.