Analysis of ZIKA Virus Tweets: Could Hadoop Platform Help in Global Health Management?

Juric, Radmila
Kim, Inhwa
Panneerselvam, Hemalatha
Tesanovic, Igor
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This paper investigates possibilities of enhancing everyday decision making in global health management, by looking at the power of twitter data and the use of big data platforms in order to collect and interpret excessive amounts of information generated in a short period of time. We use the scenario of the ZIKA virus because it has triggered a massive response through tweets and retweets. Our goal is to find out a) if we can make sense of twitter data in a global health scare and b) if information available on Twitter could help in the management and containment of the spread of the virus. The results of manual content analysis of selected tweets has been juxtaposed with the results of the manipulation of the same tweets through the Hadoop platform. We wanted to know which approach should be used for addressing public concerns about the ZIKA virus and answer a) and b) at the same time. Both approaches have their advantages and drawbacks. Therefore this paper should be used as an overview of options available for public health organizations, when they need to manipulate social media data in situations where we need to manage health on a global scale
ZIKA, Twitter, Hadoop, content-analysis
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