Based on prior research about the linguistic characteristics commonly found in misinformation, Zhou et. al conducted the following hypothesis regarding linguistic qualities, misinformation spread, and the moderating factor of media richness. 
- Compared to true information, misinformation containing more uncertainty, emotion, persuasive, or comparative words will be more widely disseminated (have more shares). 
- The difference in dissemination will be even larger when the information richness is higher (more shares for fake posts when they contain photos or videos). 

Zhou et al. Hypothesis Regarding Linguistic Characteristics and Misinformation Dissemination

Proposed by Daft and Lengel in 1986, the theory defines media richness as the information load of the content. For example, a plain text post is less rich than a post with an image. 

University of Michigan - Ann Arbor

According to a study conducted by Cheng Zhou, Kai Li, and Yanhong Lu, misinformation containing specific linguistic qualities is more likely to be shared on social media. By examining the content of fake news posts and the number of shares, they found that misinformation containing persuasive and uncertainty words were more likely to be shared than true posts. The effect was moderated by the richness of the information. 

Linguistic Traits of Misinformation Online

Zhou, C., Li, K., & Lu, Y. (2021). Linguistic characteristics and the dissemination of misinformation in social media: The moderating effect of information richness. Information Processing and Management, 58(6). https://doi.org/10.1016/j.ipm.2021.102679

Linguistic characteristics and the dissemination of misinformation in social media: The moderating effect of information richness

Media Richness Theory

Previous research has shown that misinformation tends to contain more uncertainty words and be more emotionally extreme. What is unknown is the impact these characteristics have on misinformation dissemination. To address this gap, Zhou et al. examined four linguistic characteristics thought to have an effect on misinformation dissemination, including:
- Uncertainty words
- Emotion words (positive and negative)
- Persuasive words
- Comparative words

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