Elizabeth B Blankenship1, Mary Elizabeth Goff2, Jinging Yin3, Zion Tsz Ho Tse4, King-Wa Fu5, Hai Liang6, Nitin Saroha7, Isaac Chun-Hai Fung8. 1. Graduate Student in Epidemiology and Environmental Health Sciences at the Jiann-Ping Hsu College of Public Health at Georgia Southern University in Statesboro. eb03763@georgiasouthern.edu. 2. Graduate Student in Epidemiology and Environmental Health Sciences at the Jiann-Ping Hsu College of Public Health at Georgia Southern University in Statesboro. eg01587@georgiasouthern.edu. 3. Assistant Professor of Biostatistics at the Jiann-Ping Hsu College of Public Health at Georgia Southern University in Statesboro. jyin@georgiasouthern.edu. 4. Associate Professor in the School of Electrical and Computer Engineering at the College of Engineering at the University of Georgia in Athens. ziontse@uga.edu. 5. Associate Professor at the Journalism and Media Studies Centre at the University of Hong Kong and a Visiting Associate Professor at the Massachusetts Institute of Technology Media Lab in Cambridge. kwfu@hku.hk. 6. Assistant Professor in the School of Journalism and Communication at the Chinese University of Hong Kong. hailiang@cuhk.edu.hk. 7. Graduate Student in Computer Science at the University of Georgia in Athens. ns10510@uga.edu. 8. Assistant Professor in Epidemiology and Environmental Health Sciences at the Jiann-Ping Hsu College of Public Health at Georgia Southern University in Statesboro. cfung@georgiasouthern.edu.
Abstract
INTRODUCTION: Social media platforms are important channels through which health education about the utility and safety of vaccination is conducted. OBJECTIVE: To investigate if tweets with different sentiments toward vaccination and different contents attract different levels of Twitter users' engagement (retweets). METHODS: A stratified random sample (N = 1425) of 142,891 #vaccine tweets (February 4, 2010, to November 10, 2016) was manually coded. All 201 tweets with 100 or more retweets from 194,259 #vaccineswork tweets (January 1, 2014, to April 30, 2015) were manually coded. Regression models were applied to identify factors associated with retweet frequency. RESULTS: Among #vaccine tweets, provaccine tweets (adjusted prevalence ratio = 1.5836, 95% confidence interval = 1.2130-2.0713, p < 0.001) and antivaccine tweets (adjusted prevalence ratio = 4.1280, 95% confidence interval = 3.1183-5.4901, p < 0.001) had more retweets than neutral tweets. No significant differences occurred in retweet frequency for content categories among antivaccine tweets. Among 411 links in provaccine tweets, Twitter (53; 12.9%), content curator Trap.it (14; 3.4%), and the Centers for Disease Control and Prevention (8; 1.9%) ranked as the top 3 domains. Among 325 links in antivaccine tweets, social media links were common: Twitter (44; 14.9%), YouTube (25; 8.4%), and Facebook (10; 3.4%). Among highly retweeted #vaccineswork tweets, the most common theme was childhood vaccinations (40%; 81/201); 21% mentioned global vaccination improvement/efforts (42/201); 29% mentioned vaccines can prevent outbreaks and deaths (58/201). CONCLUSION: Engaging social media key opinion leaders to facilitate health education about vaccination in their tweets may allow reaching a wider audience online.
INTRODUCTION: Social media platforms are important channels through which health education about the utility and safety of vaccination is conducted. OBJECTIVE: To investigate if tweets with different sentiments toward vaccination and different contents attract different levels of Twitter users' engagement (retweets). METHODS: A stratified random sample (N = 1425) of 142,891 #vaccine tweets (February 4, 2010, to November 10, 2016) was manually coded. All 201 tweets with 100 or more retweets from 194,259 #vaccineswork tweets (January 1, 2014, to April 30, 2015) were manually coded. Regression models were applied to identify factors associated with retweet frequency. RESULTS: Among #vaccine tweets, provaccine tweets (adjusted prevalence ratio = 1.5836, 95% confidence interval = 1.2130-2.0713, p < 0.001) and antivaccine tweets (adjusted prevalence ratio = 4.1280, 95% confidence interval = 3.1183-5.4901, p < 0.001) had more retweets than neutral tweets. No significant differences occurred in retweet frequency for content categories among antivaccine tweets. Among 411 links in provaccine tweets, Twitter (53; 12.9%), content curator Trap.it (14; 3.4%), and the Centers for Disease Control and Prevention (8; 1.9%) ranked as the top 3 domains. Among 325 links in antivaccine tweets, social media links were common: Twitter (44; 14.9%), YouTube (25; 8.4%), and Facebook (10; 3.4%). Among highly retweeted #vaccineswork tweets, the most common theme was childhood vaccinations (40%; 81/201); 21% mentioned global vaccination improvement/efforts (42/201); 29% mentioned vaccines can prevent outbreaks and deaths (58/201). CONCLUSION: Engaging social media key opinion leaders to facilitate health education about vaccination in their tweets may allow reaching a wider audience online.
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