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Using photos for public health communication: A computational analysis of the Centers for Disease Control and Prevention Instagram photos and public responses.
- Source :
- Health Informatics Journal; Sep2020, Vol. 26 Issue 3, p2159-2180, 22p
- Publication Year :
- 2020
-
Abstract
- This study aims to explore the use of Instagram by the Centers for Disease Control and Prevention, one of the representative public health authorities in the United States. For this aim, all of the photos uploaded on the Centers for Disease Control and Prevention Instagram account were crawled and the content of them were analyzed using Microsoft Azure Cognitive Services. Also, engagement was measured by the sum of numbers of likes and comments to each photo, and sentiment analysis of comments was conducted. Results suggest that the photos that can be categorized into "text" and "people" took the largest share in the Centers for Disease Control and Prevention Instagram photos. And it was found that the Centers for Disease Control and Prevention's major way of delivering messages on Instagram was to imprint key messages that call for actions for better health on photos and to provide the source of complementary information on text component of each post. It was also found that photos with more and bigger human faces had lower level of engagement than the others, and happiness and neutral emotions expressed on the faces in photos were negatively associated with engagement. The features whose high value would make the photos look splendid and gaudy were negatively correlated with engagement, but sharpness was positively correlated. [ABSTRACT FROM AUTHOR]
- Subjects :
- PUBLIC opinion
ALGORITHMS
ARTIFICIAL intelligence
COMPUTERS
CONTENT analysis
MEDICINE information services
METADATA
PHOTOGRAPHY
PROGRAMMING languages
PUBLIC health
REGRESSION analysis
RESEARCH funding
DATA analysis
SOCIAL media
ONLINE social networks
HEALTH information services
DESCRIPTIVE statistics
Subjects
Details
- Language :
- English
- ISSN :
- 14604582
- Volume :
- 26
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Health Informatics Journal
- Publication Type :
- Academic Journal
- Accession number :
- 144846474
- Full Text :
- https://doi.org/10.1177/1460458219896673