Text Versus Paratext: Understanding Individuals' Accuracy in Assessing Online Information

Abstract

Fake news has emerged as a significant problem for society. Recent research has shown that shifting attention to accuracy improves the quality of content shared by individuals, thereby helping us mitigate the harmful effects of fake news. However, the parts of a news story that can influence individuals' ability to discern the true state of information presented are understudied. We conducted an online experiment (N=408) to determine how different elements (text and paratext) of a news story influence individuals' ability to detect the true state of the information presented. The participants were presented with the headline (control), main text, graphs/images, and sharing statistics of true and fake news stories and asked to evaluate the story's accuracy based on each of these elements separately. Our findings indicate that individuals were less accurate when identifying fake news from headlines, text, and graphs/images. When asked to evaluate the story based on sharing statistics, they could distinguish fake stories from real news more accurately. Our findings also indicate that heuristics that apply to true news are ineffective for detecting the veracity of fake news. © 2023 IEEE Computer Society. All rights reserved.