Publications by authors named "Jungwon Yeo"

This study explores disaster recovery communication in the digital era. In particular, this study analyzes Twitter communication data corresponding to the 2016 Southern Louisiana flood recovery process and examines patterns and characteristics of long-term recovery communication. Based on network and sentiment analyses of the longitudinal Twitter data, the study identifies the dynamic changes in participants' numbers, dominant voices, and sentiments in social media communication during the long-term recovery process.

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International Nongovernmental Organizations (INGOs) have played critical roles in improving the quality of primary health care in ordinary time and, indeed, responding to epidemic crises in developing countries. Due to a lack of empirical research for effectiveness of their responding activities, the legitimacy and accountability of nonprofits' engagement in the health crisis as a critical responder is doubted. This paper aims to examine the effectiveness of INGOs in a context of managing a fatal epidemic outbreak of Ebola in Sierra Leone during May-November, 2014; building healthcare infrastructures, providing medical supplies, educating local residents, and training response staffs.

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While culture in emergency management has gained attention from the field of risk communication, few have systemically dealt with the nuances of general culture involved in the formation and differentiation of risk communication. To fill this gap, this research aims to first examine cultural nuances from the 2016 Louisiana flood response by primarily focusing on communications embedded in social media. The results from social network analysis and content analysis highlight that the flood response communication had strong cultural characteristics, highlighting the notion that of the cultures in Louisiana-faith-based, local authority, and nonprofits-were the prominent cultural responders in the flood response communication.

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A Bayesian influence diagram is used to analyze interactions among operational units of county health departments. This diagram, developed using Bayesian network analysis, represents a novel method of analyzing the internal performance of county health departments that were operating under the simultaneous constraints of budget cuts and increased demand for services during the H1N1 threat in California, April-July 2009. This analysis reveals the interactions among internal organizational units that degrade performance under stress or, conversely, enable a county health department to manage heavy demands effectively.

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