Abstract
Research examining the information diffusion on social media focused on the size of diffusion but has largely missed the speed by which information spreads over time. To fill this void, this study explores what intrinsic message characteristics drive information not only to reach many people but also to spread fast across social networks. Using a computational social science approach, this study collected all the original tweets from the official Twitter account of the Centers for Disease Control and Prevention (CDC) for 12 months (N = 1934). The diffusion of each tweet message was tracked for six days following its publication. The results showed that tweets with severity, efficacy, and call-for-action information achieved greater diffusion sizes and faster speed. Negative emotional words drove the information to spread widely and quickly, while positive emotional words suppressed the diffusion. Tweet messages with less affiliative words were linked to a larger size and faster speed. The study adds new insights into the dynamic processes of information diffusion and provides practical guidance to promote widespread and fast diffusion on social media.
Original language | English |
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Pages (from-to) | 37-47 |
Number of pages | 11 |
Journal | Computers in Human Behavior |
Volume | 103 |
DOIs | |
State | Published - Feb 2020 |
Bibliographical note
Publisher Copyright:© 2019 Elsevier Ltd
Keywords
- Health informatics
- Information diffusion
- Multilevel modeling
- Social media
- Speed of diffusion
ASJC Scopus subject areas
- Arts and Humanities (miscellaneous)
- Human-Computer Interaction
- General Psychology