• Journal of Digital Convergence
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• v.17 no.5
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• pp.137-143
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• 2019

Fake news is a form of misinformation that has the advantage of rapid spreading of information on media platforms that users interact with, such as social media. There has been a lot of social problems due to the recent increase in fake news. In this paper, we propose a method to detect such false news. Previous research on fake news detection mainly focused on text analysis. This research focuses on a network where social media news spreads, generates qualities with DeepWalk, a network embedding method, and classifies fake news using logistic regression analysis. We conducted an experiment on fake news detection using 211 news on the Internet and 1.2 million news diffusion network data. The results show that the accuracy of false network detection using network embedding is 10.6% higher than that of text analysis. In addition, fake news detection, which combines text analysis and network embedding, does not show an increase in accuracy over network embedding. The results of this study can be effectively applied to the detection of fake news that organizations spread online.

• Journal of Contemporary Eastern Asia
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• v.18 no.2
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• pp.118-141
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• 2019

In South Korea, as awareness of gender equality increased since the 1990s, policies for gender equality and social awareness of equality have been established. Until recently, however, the gap between men and women in social and economic activities has not reached the globally desired level and led to social conflict throughout the country. In this study, we analyze the content of online news comments to understand the public perception of gender equality and the details of gender conflict and to grasp the emergence and diffusion process of emerging issues on gender equality. We collected text data from the online news that included the word 'gender equality' posted from January 2012 to June 2017 and also collected comments on each selected news item. Through text mining and the temporal semantic network analysis, we tracked the changes in discourse on gender equality and conflict. Results revealed that gender conflicts are increasing in the online media, and the focus of conflict is shifting from 'position and role inequality' to 'opportunity inequality'.

• The Journal of the Korea Contents Association
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• v.18 no.3
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• pp.138-147
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• 2018

The network analysis is done to explore what kind if issues are diffused about earthquake and the role of social media. The types of disaster information is classified into formal and informal. The role of actor is classified based on the concentrativeness and the diffusion of issue. Youttube is functioned as a formal channel and an informal channel when disaster happened. In case of government's video, issue contractiveness is high but the diffusion is low. In case of media's video, issue contractiveness and the diffusion are all high. In case of individual channel, issue contractiveness is low, but diffusion is high. In disaster, youtube is a tool to respread the disaster issue. Government needs to try diffusion of government's news actively in disaster.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.193-203
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• 2024

In a situation where news usage through YouTube is rapidly increasing, this study investigated which attributes of issues news producers prominently report on based on the two-stage agenda setting theory to empirically investigate the influence of various news producers on YouTube. Through the research results, we confirmed that broadcasters have the influence to set the agenda and form public opinion on YouTube, and discovered the possibility of a two-stage agenda setting effect occurring in the YouTube environment. We criticized whether news producers abuse emotional words due to their partisanship when reporting political issues, and discussed that an emotional approach to political issues can have a negative impact on news users' perception of reality.

• Journal of the Korean Society for information Management
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• v.35 no.3
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• pp.41-75
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• 2018

The purpose of this study is to analyze the characteristics of Korean media on the topic of archives & records management based on time-series analysis. In this study, from January, 1999 to June, 2018, 4,680 news articles on archives & records management topics were extracted from BigKinds. In order to examine the characteristics of the media coverage on the archives & records management topic, this study was analyzed to the difference of the press coverage by period, subject, and type of the media. In addition, this study was conducted word-frequency based content analysis and semantic network analysis to investigate the content characteristics of media on the subject. Based on these results, this study was analyzed to the differences of media coverage by period, subject, and type of media. As a result, the news in the field of records management showed that there was a difference in the amount of news coverage and news contents by period, subject, and type of media. The amount of news coverage began to increase after the Presidential Records Management Act was enacted in 2007, and the largest amount of news was reported in 2013. Daily newspapers and financial newspapers reported the largest amount of news. As a result of analyzing news reports, during the first 10 years after 1999, news topics were formed around the issues arising from the application and diffusion process of the concept of archives & records management. However, since the enactment of the Presidential Records Management Act, archives & records management has become a major factor in political and social issues, and a large amount of political and social news has been reported.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.107-129
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• 2022

It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.

• Korean journal of communication and information
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• v.84
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• pp.152-188
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• 2017

This study stereotyped the media on the basis of ideological inclinations and media types and explored the news coverage through word analysis, network analysis, and frame analysis. There was no difference between conservative media and progressive media in terms of the amount of news. The conservative mainstream media considered the THAAD rumor as an unnecessary misunderstanding and a rumor based conflict of the south-south. The progressive mainstream media mentioned much about Hwang Gyoan, external influences, and lies and highlighted the government's opinion that there was external influence that spread a vicious rumor. Conservative media mentioned on the bringing about social disturbance and in case of progressive media mentioned social disturbance, and progressive media mentioned the responsibility of government and the attitude of conservative media about the diffusion of the rumor. In conclusion the press framed the THAAD rumor on the basis of their ideological inclinations instead of the role of journalist.

• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.19-39
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• 2015

Internet of Things (IoT) is expected to provide efficiency and convenience in human life by integrating the Internet into the things that we use in daily lives. IoT can not only create new businesses but also can bring great changes in our lives thanks to the various ways of technical application: defining relationships among things or automatic use of technology by analyzing the usage pattern. This study uses the qualitative research of interviewing the experts to predict the changes that IoT technology is expected to bring in our lives. In addition, this paper analyzes news articles about internet of things in Korea using text-network analysis. This study also discusses the factors which need to be considered to put IoT into successful use in business contexts.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.5
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• pp.145-156
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• 2022

In recent years, as there is growing concern with ESG (Environmental, Social, and Governance), the strategic direction of business management is changing from maximizing shareholders wealth to maximizing stakeholders value. ESG is reshaping a corporation's supply chain management strategies. The purpose of this study is to explore the ESG challenges in supply chain management. As a result of network text analysis and topic modeling analysis on 3226 news articles, 'Suppliers', 'Sustainability', 'Shared Growth' 'Carbon Neutral', 'Safety and Health', 'Responsible Business Alliance', 'Supply Chain Due Diligence Law' were identified as the main issue. Since ESG initiatives in the supply chain are not limited to the efforts of individual firms, future research should focus on figuring out what difficulties and challenges exist in the diffusion of ESG practices along multi-tiered supply chains, and how to overcome them.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.269-287
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• 2016

This study explores of press report on the death of Beongen Yoo based on network analysis and how issue diffuses via Internet and SNS in mainstream news and conservative channels of comprehensive programming. Issue salience, word's visibility and word's connectivity are the main keyword and analysis criteria of this study. Conservative channel of comprehensive programming focused on the surrounding information rather than core information compared to Mainstream media, Conservative channels of comprehensive media was interested in Yu, Beongeon, an article left, brand, rumor of a body and Mainstream media focused on the results of DNA test. Mainstream media covers this case as the discovery of the Yu, Beongeon body, Mainstream media reported as 'the discovery of the body frame, conservative channels of comprehensive programming reports as blame of investigation at the first stage. The former focuses on the cause of death and the latter focuses on the raising of strong doubts frame at the second stage. In case of the third stage the latter covered on the emphasis of the surrounding information. They frames the issue differently based on network analysis. The view point of conservative channel of comprehensive programming is diffused via SNS. This study highlights the role of journalist of mainstream media in the process of agenda-setting