Health Communication Research 2021 KCI Impact Factor : 0.33

Korean | English

pISSN : 2093-2707 / eISSN : 2671-5856
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2019, Vol.18, No.1

  • 1.

    A Content Analysis of U.S. Non-Profit Organizations’ College Drinking Awareness Facebook Pages: Interactivity and Engagement

    Kang, Hannah | 2019, 18(1) | pp.1~30 | number of Cited : 0
    Abstract PDF
    The purpose of this study is to analyze contents of Facebook for U.S. non-profit organizations related to college drinking, in order to understand how and to what extent the non-profit organizations related to U.S. college students’ drinking have used Facebook to target and communicate with people to increase their engagements in the social media. Based on the analysis of a total of 153 posts in the top five Facebook pages of U.S. non-profit organizations for a one year period in the area of college drinking, two types of interactivity were examined: interactive feature and message type. The results showed that the most common interactive feature the posts used was photo or image sharing (92.2%). In terms of message type, about 50% of the posts contained a message regarding calls for involvement, and threat appeal was used most. Moreover, some relationships between interactive feature/ message type and engagement were found. Results indicate that non-profit organizations related to college drinking have not utilized Facebook’s interactive features and messages effectively to attract U.S. college students to engage in their Facebook pages.
  • 2.

    Social Media and Influenza Emergency: Content Analysis of Tweets during the 2015 MERS Outbreak in Korea

    Byoungkwan Lee , Hyun Jung Oh , Hyunmi Baek and 1 other persons | 2019, 18(1) | pp.31~62 | number of Cited : 0
    Abstract PDF
    The risk perception is a key issue for effective health risk communication. This study gathers and analyzes MERS-related tweets in order to monitor and understand the public perception on Twitter during the MERS outbreak of 2015 in South Korea. The main purpose of study is to identify and describe the changes in the number of MERS-related tweets. Using Naïve Bayesian classifiers, this study investigates the public sentiments on Twitter and examines how the sentiments affect the spreading volume, duration, and speed of MERS-related tweets. The results show dramatic changes in the amount of MERS-related tweets during these sequences of time periods. The results of sentiment analysis also showed that the emotional response of the public on Twitter had changed in a variety of ways depending on the types of triggering events. Moreover, an emotional (positive or negative) message in social media seems to receive more attention and feedback than a non-emotional message and induce cognitive and arousal-related effects that trigger sharing behavior in social media communication.