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

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

doi:10.2196/publichealth.8737

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

JMIR Public Health Surveill. 2018 Apr 2;4(2):e33. doi: 10.2196/publichealth.8737.

Authors

Isaac Chun-Hai Fung^#¹, Ashley M Jackson^#¹, Lindsay A Mullican^#¹, Elizabeth B Blankenship¹, Mary Elizabeth Goff¹, Amy J Guinn², Nitin Saroha³, Zion Tsz Ho Tse⁴

Affiliations

¹ Department of Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA, United States.
² Office of Advanced Molecular Detection, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States.
³ Department of Computer Science, The University of Georgia, Athens, GA, United States.
⁴ School of Electrical and Computer Engineering, College of Engineering, The University of Georgia, Athens, GA, United States.

^# Contributed equally.

Abstract

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.

Keywords: communications media; health communication; social media.

©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.