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A Semantic Network Analysis Of News Reports On An Emerging Infectious Disease By Multidrug-resistant Microorganism

K. Park, Gui-ohk Lee, Myungil Choi
Published 2014 · Medicine

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The present study performed semantic network analysis of the keywords in the headlines of newspapers to investigate the media coverage of the multidrug-resistant microorganisms(MDROs) which is resistant to antibiotics. For this purpose, 229 news stories on MDROs in 28 newspapers from June 1, 2010 to December 31, 2011 were analyzed. The news stories were gathered from the Korea Press Foundation's news database, KINDS ( and websites of Korean newspapers. The analysis of the keywords revealed ‘superbacteria’ appeared most frequently (n=155) followed by ‘infection' (n=63) which arouses fear among readers. While network was structured with the keywords such as ‘domestic’, ‘multidrug-resistant microorganisms’, ‘first’, ‘antibiotics’, ‘outbreak’ and ‘infection’, the keywords such as ‘MDROs related stocks’, ‘medical staff’, and ‘safety’ were on the periphery of the network.
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