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Nursing Management

March 2013, Volume 44 Number 3 , p 10 - 11


  • Charles Boicey MS, RN-BC, CPHIMS


MappyHealth, a public health surveillance web application and social media collaboration, started with a single tweet from Brian Norris, MBA, BGS, RN-BC: "Do I have any connections out there who are familiar with the Twitter API?"1 Answering that tweet was Mark Silverberg, Management of Information Systems student at George Washington University. Brian Norris and Mark Silverberg then reached out to this article's author, and the MappyHealth team was formed.Public health officials looking back on the 2009 H1N1 pandemic and Haitian cholera outbreak realized that social media trends could potentially indicate disease outbreak trends quicker than traditional methods of public health reporting. This-coupled with direct requests for social media surveillance tools from public health organizations-is the reason that Department of Health and Human Services Assistant Secretary for Preparedness and Response Nicole Lurie, MD, MSPH, created the "Now Trending: #Health in My Community" contest.2 The contest challenged innovators to develop a platform that utilizes publically available Twitter data to deliver the top five trending illnesses for a specific geographic region. Thirty-three teams entered the contest, and MappyHealth was selected as the winner.MappyHealth is a web-based application that provides a variety of analytical views of disease-oriented tweets. The first, and most obvious, challenge of working with social media data is that they're unstructured and seemingly endless. In June 2012, it was estimated that 400 million tweets per day are created, with anticipation of almost 2 billion users on Twitter.3 For any organization attempting to utilize social media data, there are several key challenges they'll face. MappyHealth had to address the following questions as the platform was constructed: * What problem (question) is being solved? * How will users of the platform utilize the information provided? * How's the data best visualized? * What semantics will be meaningful?

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