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Contents, Followers, and Retweets of the Centers for Disease Control and Prevention’s Office of Advanced Molecular Detection (@CDC_AMD) Twitter Profile: Cross-Sectional Study
BACKGROUND: The Office of Advanced Molecular Detection (OAMD), Centers for Disease Control and Prevention (CDC), manages a Twitter profile (@CDC_AMD). To our knowledge, no prior study has analyzed a CDC Twitter handle’s entire contents and all followers. OBJECTIVE: This study aimed to describe the c...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5902693/ https://www.ncbi.nlm.nih.gov/pubmed/29610112 http://dx.doi.org/10.2196/publichealth.8737 |
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author | Fung, Isaac Chun-Hai Jackson, Ashley M Mullican, Lindsay A Blankenship, Elizabeth B Goff, Mary Elizabeth Guinn, Amy J Saroha, Nitin Tse, Zion Tsz Ho |
author_facet | Fung, Isaac Chun-Hai Jackson, Ashley M Mullican, Lindsay A Blankenship, Elizabeth B Goff, Mary Elizabeth Guinn, Amy J Saroha, Nitin Tse, Zion Tsz Ho |
author_sort | Fung, Isaac Chun-Hai |
collection | PubMed |
description | BACKGROUND: The Office of Advanced Molecular Detection (OAMD), Centers for Disease Control and Prevention (CDC), manages a Twitter profile (@CDC_AMD). To our knowledge, no prior study has analyzed a CDC Twitter handle’s entire contents and all followers. OBJECTIVE: This study aimed to describe the contents and followers of the Twitter profile @CDC_AMD and to assess if attaching photos or videos to tweets posted by @CDC_AMD would increase retweet frequency. METHODS: Data of @CDC_AMD were retrieved on November 21, 2016. All followers (N=809) were manually categorized. All tweets (N=768) were manually coded for contents and whether photos or videos were attached. Retweet count for each tweet was recorded. Negative binomial regression models were applied to both the original and the retweet corpora. RESULTS: Among the 809 followers, 26.0% (210/809) were individual health professionals, 11.6% (94/809) nongovernmental organizations, 3.3% (27/809) government agencies’ accounts, 3.3% (27/809) accounts of media organizations and journalists, and 0.9% (7/809) academic journals, with 54.9% (444/809) categorized as miscellaneous. A total of 46.9% (360/768) of @CDC_AMD’s tweets referred to the Office’s website and their current research; 17.6% (135/768) referred to their scientists’ publications. Moreover, 80% (69/86) of tweets retweeted by @CDC_AMD fell into the miscellaneous category. In addition, 43.4% (333/768) of the tweets contained photos or videos, whereas the remaining 56.6% (435/768) did not. Attaching photos or videos to original @CDC_AMD tweets increases the number of retweets by 37% (probability ratio=1.37, 95% CI 1.13-1.67, P=.002). Content topics did not explain or modify this association. CONCLUSIONS: This study confirms CDC health communicators’ experience that original tweets created by @CDC_AMD Twitter profile sharing images or videos (or their links) received more retweets. The current policy of attaching images to tweets should be encouraged. |
format | Online Article Text |
id | pubmed-5902693 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-59026932018-04-24 Contents, Followers, and Retweets of the Centers for Disease Control and Prevention’s Office of Advanced Molecular Detection (@CDC_AMD) Twitter Profile: Cross-Sectional Study Fung, Isaac Chun-Hai Jackson, Ashley M Mullican, Lindsay A Blankenship, Elizabeth B Goff, Mary Elizabeth Guinn, Amy J Saroha, Nitin Tse, Zion Tsz Ho JMIR Public Health Surveill Original Paper BACKGROUND: The Office of Advanced Molecular Detection (OAMD), Centers for Disease Control and Prevention (CDC), manages a Twitter profile (@CDC_AMD). To our knowledge, no prior study has analyzed a CDC Twitter handle’s entire contents and all followers. OBJECTIVE: This study aimed to describe the contents and followers of the Twitter profile @CDC_AMD and to assess if attaching photos or videos to tweets posted by @CDC_AMD would increase retweet frequency. METHODS: Data of @CDC_AMD were retrieved on November 21, 2016. All followers (N=809) were manually categorized. All tweets (N=768) were manually coded for contents and whether photos or videos were attached. Retweet count for each tweet was recorded. Negative binomial regression models were applied to both the original and the retweet corpora. RESULTS: Among the 809 followers, 26.0% (210/809) were individual health professionals, 11.6% (94/809) nongovernmental organizations, 3.3% (27/809) government agencies’ accounts, 3.3% (27/809) accounts of media organizations and journalists, and 0.9% (7/809) academic journals, with 54.9% (444/809) categorized as miscellaneous. A total of 46.9% (360/768) of @CDC_AMD’s tweets referred to the Office’s website and their current research; 17.6% (135/768) referred to their scientists’ publications. Moreover, 80% (69/86) of tweets retweeted by @CDC_AMD fell into the miscellaneous category. In addition, 43.4% (333/768) of the tweets contained photos or videos, whereas the remaining 56.6% (435/768) did not. Attaching photos or videos to original @CDC_AMD tweets increases the number of retweets by 37% (probability ratio=1.37, 95% CI 1.13-1.67, P=.002). Content topics did not explain or modify this association. CONCLUSIONS: This study confirms CDC health communicators’ experience that original tweets created by @CDC_AMD Twitter profile sharing images or videos (or their links) received more retweets. The current policy of attaching images to tweets should be encouraged. JMIR Publications 2018-04-02 /pmc/articles/PMC5902693/ /pubmed/29610112 http://dx.doi.org/10.2196/publichealth.8737 Text en ©Isaac Chun-Hai Fung, Ashley M Jackson, Lindsay A Mullican, Elizabeth B Blankenship, Mary Elizabeth Goff, Amy J Guinn, Nitin Saroha, Zion Tsz Ho Tse. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 02.04.2018. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on http://publichealth.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Fung, Isaac Chun-Hai Jackson, Ashley M Mullican, Lindsay A Blankenship, Elizabeth B Goff, Mary Elizabeth Guinn, Amy J Saroha, Nitin Tse, Zion Tsz Ho Contents, Followers, and Retweets of the Centers for Disease Control and Prevention’s Office of Advanced Molecular Detection (@CDC_AMD) Twitter Profile: Cross-Sectional Study |
title | Contents, Followers, and Retweets of the Centers for Disease Control and Prevention’s Office of Advanced Molecular Detection (@CDC_AMD) Twitter Profile: Cross-Sectional Study |
title_full | Contents, Followers, and Retweets of the Centers for Disease Control and Prevention’s Office of Advanced Molecular Detection (@CDC_AMD) Twitter Profile: Cross-Sectional Study |
title_fullStr | Contents, Followers, and Retweets of the Centers for Disease Control and Prevention’s Office of Advanced Molecular Detection (@CDC_AMD) Twitter Profile: Cross-Sectional Study |
title_full_unstemmed | Contents, Followers, and Retweets of the Centers for Disease Control and Prevention’s Office of Advanced Molecular Detection (@CDC_AMD) Twitter Profile: Cross-Sectional Study |
title_short | Contents, Followers, and Retweets of the Centers for Disease Control and Prevention’s Office of Advanced Molecular Detection (@CDC_AMD) Twitter Profile: Cross-Sectional Study |
title_sort | contents, followers, and retweets of the centers for disease control and prevention’s office of advanced molecular detection (@cdc_amd) twitter profile: cross-sectional study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5902693/ https://www.ncbi.nlm.nih.gov/pubmed/29610112 http://dx.doi.org/10.2196/publichealth.8737 |
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