• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.335-346
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• 2015

The purpose of this study is to compare not only network influence of individual coauthor but also the types and properties of two coauthor networks of Communications for Statistical Applications and Methods and the Korean Journal of Applied Statistics which are published by the Korean Statistical Society using social network analysis.As the result of two network structure comparison, density, inclusiveness, reciprocity and clustering coefficient which represent the type of coauthor networks show almost similar values and the Korean Journal of Applied Statistics has bigger values in average degree, average distance and diameter because it has more nodes than Communications for Statistical Applications and Methods. Finally two journals have very similar type of coauthor network. In the comparison of network centrality of two coauthor networks, closeness centrality and betweenness centrality of the Korean Journal of Applied Statistics are bigger than those of Communications for Statistical Applications and Methods at the statistical significance level 0.05. The coauthor network of the Korean Journal of Applied Statistics has faster information delivery and stronger betweenness than that of Communications for Statistical Applications.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.75-94
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• 2011

In this paper, we explore the information diffusion mechanism under social network environments by investigating the effect of message characteristics on the volume and speed of retweeting in Twitter, a popular online social media service. To this end, we select eight main keywords (i.e., '무상급식', '반값등록금', '나가수', '평창', '김연아', '박태환', '아이폰', '갤럭시') that have been popular on online social media in recent days. Each keyword represents various social aspects of Korea that recently grab people's attention such as political issues, entertainment, sports celebrities, and the latest digital products, and eventually holds distinctive message characteristics. Analyzing the frequency and velocity of retweeting for each keyword, we find that more than half of the sample messages posted on Twitter contain personal opinions for the certain keyword, but we also find that the tweets which include objective messages with hyperlink are the fastest ones when being retweeted by other followers. In overall, when being retweeted, the group of messages related to the certain keyword present distinctive diffusion patterns and speed according to message characteristics. From academic perspective, the findings in the study broaden our theoretical knowledge of information diffusion mechanism over online social media. For practitioners, the results also provide managerial implications regarding how to strategically utilize online social media for marketing communications with customers.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.195-200
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• 2019

Nowadays as the use of mobile communication devices such as smart phones and tablets and the use of Computer is expanded, data is being collected exponentially on the Internet. In addition, due to the development of SNS, users can freely communicate with each other and share information in various fields, so various opinions are accumulated in the from of big data. Accordingly, big data analysis techniques are being used to find out the difference between the response of the general public and the response of the media. In this paper, we analyzed the public response in SNS about child allowance and childbirth grant and analyzed the response of the media. Therefore we gathered articles and comments of users which were posted on Twitter for a certain period of time and crawling the news articles and applied sentiment analysis. From these data, we compared the opinion of the public posted on SNS with the response of the media expressed in news articles. As a result, we found that there is a different response to some national policy between the public and the media.