Isaac Chun-Hai Fung1, Carmen Hope Duke2, Kathryn Cameron Finch2, Kassandra Renee Snook2, Pei-Ling Tseng2, Ana Cristina Hernandez3, Manoj Gambhir4, King-Wa Fu5, Zion Tsz Ho Tse6. 1. Department of Epidemiology, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA. Electronic address: cfung@georgiasouthern.edu. 2. Department of Epidemiology, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA. 3. Department of Foreign Languages and Department of Biology, Georgia Southern University, Statesboro, GA. 4. Epidemiological Modelling Unit, Department of Epidemiology and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia. 5. Journalism and Media Studies Centre, The University of Hong Kong, Hong Kong Special Administrative Region of the People's Republic of China. 6. College of Engineering, The University of Georgia, Athens, GA.
Abstract
OBJECTIVES: We systematically reviewed existing research pertinent to Ebola virus disease and social media, especially to identify the research questions and the methods used to collect and analyze social media. METHODS: We searched 6 databases for research articles pertinent to Ebola virus disease and social media. We extracted the data using a standardized form. We evaluated the quality of the included articles. RESULTS: Twelve articles were included in the main analysis: 7 from Twitter with 1 also including Weibo, 1 from Facebook, 3 from YouTube, and 1 from Instagram and Flickr. All the studies were cross-sectional. Eleven of the 12 articles studied ≥ 1of these 3 elements of social media and their relationships: themes or topics of social media contents, meta-data of social media posts (such as frequency of original posts and reposts, and impressions) and characteristics of the social media accounts that made these posts (such as whether they are individuals or institutions). One article studied how news videos influenced Twitter traffic. Twitter content analysis methods included text mining (n = 3) and manual coding (n = 1). Two studies involved mathematical modeling. All 3 YouTube studies and the Instagram/Flickr study used manual coding of videos and images, respectively. CONCLUSIONS: Published Ebola virus disease-related social media research focused on Twitter and YouTube. The utility of social media research to public health practitioners is warranted. Copyright Â
OBJECTIVES: We systematically reviewed existing research pertinent to Ebola virus disease and social media, especially to identify the research questions and the methods used to collect and analyze social media. METHODS: We searched 6 databases for research articles pertinent to Ebola virus disease and social media. We extracted the data using a standardized form. We evaluated the quality of the included articles. RESULTS: Twelve articles were included in the main analysis: 7 from Twitter with 1 also including Weibo, 1 from Facebook, 3 from YouTube, and 1 from Instagram and Flickr. All the studies were cross-sectional. Eleven of the 12 articles studied ≥ 1of these 3 elements of social media and their relationships: themes or topics of social media contents, meta-data of social media posts (such as frequency of original posts and reposts, and impressions) and characteristics of the social media accounts that made these posts (such as whether they are individuals or institutions). One article studied how news videos influenced Twitter traffic. Twitter content analysis methods included text mining (n = 3) and manual coding (n = 1). Two studies involved mathematical modeling. All 3 YouTube studies and the Instagram/Flickr study used manual coding of videos and images, respectively. CONCLUSIONS: Published Ebola virus disease-related social media research focused on Twitter and YouTube. The utility of social media research to public health practitioners is warranted. Copyright Â
Authors: Carmina Castellano-Tejedor; María Torres-Serrano; Andrés Cencerrado Journal: Int J Environ Res Public Health Date: 2022-04-09 Impact factor: 4.614
Authors: Isaac Chun-Hai Fung; Elizabeth B Blankenship; Jennifer O Ahweyevu; Lacey K Cooper; Carmen H Duke; Stacy L Carswell; Ashley M Jackson; Jimmy C Jenkins; Emily A Duncan; Hai Liang; King-Wa Fu; Zion Tsz Ho Tse Journal: Perm J Date: 2019-12-06
Authors: Corey H Basch; Isaac Chun-Hai Fung; Rodney N Hammond; Elizabeth B Blankenship; Zion Tsz Ho Tse; King-Wa Fu; Patrick Ip; Charles E Basch Journal: J Prev Med Public Health Date: 2017-01-26
Authors: 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 Journal: JMIR Public Health Surveill Date: 2018-04-02