- About
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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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Showing 1 to 2 of 2 (0.048 seconds)Spelling suggestions: "subject:"coveillance"" "subject:"bienveillance""
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Pandemics in the Age of Twitter: A Content Analysis of the 2009 H1N1 OutbreakChew, Cynthia 16 December 2010 (has links)
This thesis reports on the use of Twitter during the 2009 H1N1 pandemic to explore its use as an “infoveillance” approach complementary to traditional surveys and content analysis. This study aimed to: 1) report on the use of “H1N1” versus “swine flu”, 2) conduct a qualitative analysis of tweet content, and 3) assess the feasibility of Twitter as a real-time content, sentiment, and public attention trend tracking tool.
A manual content analysis of tweets revealed that H1N1 resources were the most commonly shared. Few tweets provided inaccurate information. News websites were the most popular resources while official agencies were rarely referenced directly. Our automated analysis correlated well with manual results and showed that Twitter activity was influenced by external events.
This study describes the character and quality of Twitter communications during the H1N1 pandemic, and illustrates the potential of using social media to conduct real-time “infodemiology” studies for public health.
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| 2 |
Pandemics in the Age of Twitter: A Content Analysis of the 2009 H1N1 OutbreakChew, Cynthia 16 December 2010 (has links)
This thesis reports on the use of Twitter during the 2009 H1N1 pandemic to explore its use as an “infoveillance” approach complementary to traditional surveys and content analysis. This study aimed to: 1) report on the use of “H1N1” versus “swine flu”, 2) conduct a qualitative analysis of tweet content, and 3) assess the feasibility of Twitter as a real-time content, sentiment, and public attention trend tracking tool.
A manual content analysis of tweets revealed that H1N1 resources were the most commonly shared. Few tweets provided inaccurate information. News websites were the most popular resources while official agencies were rarely referenced directly. Our automated analysis correlated well with manual results and showed that Twitter activity was influenced by external events.
This study describes the character and quality of Twitter communications during the H1N1 pandemic, and illustrates the potential of using social media to conduct real-time “infodemiology” studies for public health.
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