Santosh Vijaykumar1, Glen Nowak2, Itai Himelboim2, Yan Jin2. 1. Department of Psychology, Northumbria University, Newcastle upon Tyne, United Kingdom. Electronic address: santosh.vijaykumar@northumbria.ac.uk. 2. Grady College of Journalism and Mass Communication, University of Georgia, Athens, Georgia.
Abstract
BACKGROUND: This paper goes beyond detecting specific themes within Zika-related chatter on Twitter, to identify the key actors who influence the diffusive process through which some themes become more amplified than others. METHODS: We collected all Zika-related tweets during the 3 months immediately after the first U.S. case of Zika. After the tweets were categorized into 12 themes, a cross-section were grouped into weekly datasets, to capture 12 amplifier/user groups, and analyzed by 4 amplification modes: mentions, retweets, talkers, and Twitter-wide amplifiers. RESULTS: We analyzed 3,057,130 tweets in the United States and categorized 4997 users. The most talked about theme was Zika transmission (~58%). News media, public health institutions, and grassroots users were the most visible and frequent sources and disseminators of Zika-related Twitter content. Grassroots users were the primary sources and disseminators of conspiracy theories. CONCLUSIONS: Social media analytics enable public health institutions to quickly learn what information is being disseminated, and by whom, regarding infectious diseases. Such information can help public health institutions identify and engage with news media and other active information providers. It also provides insights into media and public concerns, accuracy of information on Twitter, and information gaps. The study identifies implications for pandemic preparedness and response in the digital era and presents the agenda for future research and practice.
BACKGROUND: This paper goes beyond detecting specific themes within Zika-related chatter on Twitter, to identify the key actors who influence the diffusive process through which some themes become more amplified than others. METHODS: We collected all Zika-related tweets during the 3 months immediately after the first U.S. case of Zika. After the tweets were categorized into 12 themes, a cross-section were grouped into weekly datasets, to capture 12 amplifier/user groups, and analyzed by 4 amplification modes: mentions, retweets, talkers, and Twitter-wide amplifiers. RESULTS: We analyzed 3,057,130 tweets in the United States and categorized 4997 users. The most talked about theme was Zika transmission (~58%). News media, public health institutions, and grassroots users were the most visible and frequent sources and disseminators of Zika-related Twitter content. Grassroots users were the primary sources and disseminators of conspiracy theories. CONCLUSIONS: Social media analytics enable public health institutions to quickly learn what information is being disseminated, and by whom, regarding infectious diseases. Such information can help public health institutions identify and engage with news media and other active information providers. It also provides insights into media and public concerns, accuracy of information on Twitter, and information gaps. The study identifies implications for pandemic preparedness and response in the digital era and presents the agenda for future research and practice.
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