Tweeting about measles during stages of an outbreak: A semantic network approach to the framing of an emerging infectious disease.
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BACKGROUND: The public increasingly uses social media not only to look for information about emerging infectious diseases (EIDs), but also to share opinions, emotions, and coping strategies. Identifying the frames used in social media discussion about EIDs will allow public health agencies to assess public opinions and sentiments. METHOD: This study examined how the public discussed measles during the measles outbreak in the United States during early 2015 that originated in Disneyland Park in Anaheim, CA, through a semantic network analysis of the content of around 1 million tweets using KH coder. RESULTS: Four frames were identified based on word frequencies and co-occurrence: news update, public health, vaccination, and political. The prominence of each individual frame changed over the corse of the pre-crisis, initial, maintenance, and resolution stages of the outbreak. CONCLUSIONS: This study proposed and tested a method for assessing the frames used in social media discussions about EIDs based on the creation, interpretation, and quantification of semantic networks. Public health agencies could use social media outlets, such as Twitter, to assess how the public makes sense of an EID outbreak and to create adaptive messages in communicating with the public during different stages of the crisis.
