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James Powell, Matthew Hopkins (2015)
A librarian's guide to graphs, data and the semantic web
- Publisher
- Wiley
- Copyright
- © 2022 John Wiley & Sons Ltd.
- ISSN
- 0749-6753
- eISSN
- 1099-1751
- DOI
- 10.1002/hpm.3500
- Publisher site
- See Article on Publisher Site
Abstract
This study highlights how people get important information on COVID‐19 according to age groups by employing social network analysis for Twitter. First, people have different key players according to the age groups. For example, while universities and journals play a crucial role in the adults' networks, news media have a significant impact on the elderly's networks. Second, people have different characteristics of social network groups according to age. For example, people belong to small groups, and barely communicate with others across the groups in the teens' networks, whereas people in each group have strong communication networks with other groups in the elderly's networks. Third, this study shows that people utilise different domains to share COVID‐19 information according to age. For example, while twitter.com ranks first in the children, teens, and elderly's networks, cnn.com places first in the adults' networks.
Journal
The International Journal of Health Planning and Management – Wiley
Published: Sep 1, 2022
Keywords: age; coronavirus; COVID‐19; social network analysis; twitter