Braydon J Schaible1, Kassandra R Snook1, Jingjing Yin1, Ashley M Jackson1, Jennifer O Ahweyevu1, Muhling Chong1, Zion Tsz Ho Tse2, Hai Liang3,4, King-Wa Fu3, Isaac Chun-Hai Fung1. 1. Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University in Statesboro. 2. School of Electrical Engineering and Computer Engineering, College of Engineering, University of Georgia, Athens. 3. Journalism and Media Studies Centre, University of Hong Kong. 4. School of Journalism and Communication, Chinese University of Hong Kong.
Abstract
INTRODUCTION: Twitter and media coverage on poliomyelitis help maintain global support for its eradication. OBJECTIVE: To test our hypothesis that themes of polio-related tweets and media articles would differ by location of interest (hashtag of country name mentioned in the tweet; country name mentioned in media articles) but would be similar to each other (tweets and media articles) for each location of interest. METHODS: We retrospectively examined a 40% random sample of Twitter data containing the hashtag #polio from January 1, 2014, to April 30, 2015 (N = 79,333), from which we extracted 5 subcorpora each with a co-occurring hashtag #India (n = 5027), #Iraq (n = 1238), #Nigeria (n = 1364), #Pakistan (n = 11,427), and #Syria (n = 2952). We also retrieved and categorized 73 polio-related English-language news stories from within the same timeframe. We assessed the association between polio-related English news themes and the Twitter content. Descriptive analyses and unsupervised machine learning (latent Dirichlet allocation modeling) were conducted on the 5 Twitter subcorpora. RESULTS: The results of the latent Dirichlet allocation modeling on the specific subcorpora with country co-occurring hashtags showed significant differences between the 5 countries in terms of content. English mass media content focused largely on violence/conflicts and cases of polio, whereas social media focused on eradication and vaccination efforts along with celebrations. DISCUSSION: Contrary to our hypothesis, our evidence suggests Twitter content differs significantly from English mass media content. Evidence from our study helps inform media monitoring and communications surveillance during global public health crises, such as infectious disease outbreaks, as well as reactions to health promotion campaigns.
INTRODUCTION: Twitter and media coverage on poliomyelitis help maintain global support for its eradication. OBJECTIVE: To test our hypothesis that themes of polio-related tweets and media articles would differ by location of interest (hashtag of country name mentioned in the tweet; country name mentioned in media articles) but would be similar to each other (tweets and media articles) for each location of interest. METHODS: We retrospectively examined a 40% random sample of Twitter data containing the hashtag #polio from January 1, 2014, to April 30, 2015 (N = 79,333), from which we extracted 5 subcorpora each with a co-occurring hashtag #India (n = 5027), #Iraq (n = 1238), #Nigeria (n = 1364), #Pakistan (n = 11,427), and #Syria (n = 2952). We also retrieved and categorized 73 polio-related English-language news stories from within the same timeframe. We assessed the association between polio-related English news themes and the Twitter content. Descriptive analyses and unsupervised machine learning (latent Dirichlet allocation modeling) were conducted on the 5 Twitter subcorpora. RESULTS: The results of the latent Dirichlet allocation modeling on the specific subcorpora with country co-occurring hashtags showed significant differences between the 5 countries in terms of content. English mass media content focused largely on violence/conflicts and cases of polio, whereas social media focused on eradication and vaccination efforts along with celebrations. DISCUSSION: Contrary to our hypothesis, our evidence suggests Twitter content differs significantly from English mass media content. Evidence from our study helps inform media monitoring and communications surveillance during global public health crises, such as infectious disease outbreaks, as well as reactions to health promotion campaigns.
Authors: Isaac Chun-Hai Fung; King-Wa Fu; Chung-Hong Chan; Benedict Shing Bun Chan; Chi-Ngai Cheung; Thomas Abraham; Zion Tsz Ho Tse Journal: Public Health Rep Date: 2016 May-Jun Impact factor: 2.792
Authors: Isaac Chun-Hai Fung; Ashley M Jackson; Jennifer O Ahweyevu; Jordan H Grizzle; Jingjing Yin; Zion Tsz Ho Tse; Hai Liang; Juliet N Sekandi; King-Wa Fu Journal: Ann Glob Health Date: 2017-10-26 Impact factor: 2.462
Authors: King-Wa Fu; Hai Liang; Nitin Saroha; Zion Tsz Ho Tse; Patrick Ip; Isaac Chun-Hai Fung Journal: Am J Infect Control Date: 2016-08-24 Impact factor: 2.918
Authors: Sara R Bedrosian; Cathy E Young; Laura A Smith; Joanne D Cox; Craig Manning; Laura Pechta; Jana L Telfer; Molly Gaines-McCollom; Kathy Harben; Wendy Holmes; Keri M Lubell; Jennifer H McQuiston; Kristen Nordlund; John O'Connor; Barbara S Reynolds; Jessica A Schindelar; Gene Shelley; Katherine Lyon Daniel Journal: MMWR Suppl Date: 2016-07-08
Authors: Sunil Bahl; Rakesh Kumar; Nata Menabde; Arun Thapa; Jeffrey McFarland; Virginia Swezy; Rudolph H Tangermann; Hamid S Jafari; Linda Elsner; Steven G F Wassilak; Olen M Kew; Stephen L Cochi Journal: MMWR Morb Mortal Wkly Rep Date: 2014-10-24 Impact factor: 17.586
Authors: Wen-ying Sylvia Chou; Yvonne M Hunt; Ellen Burke Beckjord; Richard P Moser; Bradford W Hesse Journal: J Med Internet Res Date: 2009-11-27 Impact factor: 5.428
Authors: Gerlant van Berlaer; Abdallah Mohamed Elsafti; Mohammad Al Safadi; Saad Souhil Saeed; Ronald Buyl; Michel Debacker; Atef Redwan; Ives Hubloue Journal: PLoS One Date: 2017-09-08 Impact factor: 3.240