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Easy-access online social media metrics are associated with misinformation sharing activity
Title / Series / Name
Scientific Reports
Publication Volume
15
Publication Issue
1
Pages
Editors
Keywords
Cognitive load
Digital literacy
Misinformation
Social considerations
Social media
X
Multidisciplinary
Digital literacy
Misinformation
Social considerations
Social media
X
Multidisciplinary
URI
https://hdl.handle.net/20.500.14018/28708
Abstract
Misinformation poses a significant challenge studied extensively by researchers, yet acquiring data to identify primary sharers is time-consuming and challenging. To address this, we propose a low-barrier approach to differentiate social media users who are more likely to share misinformation from those who are less likely. Leveraging insights from previous studies, we demonstrate that easy-access online social network metrics–average daily tweet count, and account age–can be leveraged to help identify potential low factuality content spreaders on X (previously known as Twitter). We find that higher tweet frequency is positively associated with low factuality in shared content, while account age is negatively associated with it. We also find that some of the effects differ depending on the number of accounts a user follows. Our findings show that relying on these easy-access social network metrics could serve as a low-barrier approach for initial identification of users who are more likely to spread misinformation, and therefore contribute to combating misinformation effectively on social media platforms.
Topic
Publisher
Place of Publication
Type
Journal article
Date
2025-11
Language
ISBN
Identifiers
10.1038/s41598-025-25049-6