• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.317-340
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• 2023

In a business context, ESG is defined as the use of environmental, social, and governance factors to assess a firm's progress in terms of sustainability. Social media has enabled the public to actively share firms' good and/or bad deeds, increasing public interest in ESG management. Therefore, this study aimed to investigate the association of firm performances with the respective sentiments towards each of environmental, social, and governance activities, as well as comprehensive ESG sentiments, which encompass all environmental, social, and governance sentiments. This study used panel regression models to examine the relationship between social media ESG sentiment and the Return on Assets (ROA) and Return on Equity (ROE) of 143 companies listed on the KOSPI 200. We collected data from 2018 to 2021, including sentiment data from a variety of social media channels, such as online communities, Instagram, blogs, Twitter, and other news. The results indicated that firm performance is significantly related to respective ESG and comprehensive ESG sentiments. This study has several implications. By using data from various social media channels, it presents an unbiased view of public ESG sentiment, rather than relying on ESG ratings, which may be influenced by rating agencies. Furthermore, the findings can be used to help firms determine the direction of their ESG management. Therefore, this study provides theoretical and practical insights for researchers and firms interested in ESG management.

• Journal of Korean Library and Information Science Society
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• v.48 no.3
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• pp.113-130
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• 2017

The goal of this study is to propose the approaches to improve the voters' awareness by analyzing the voters' awareness on the fake news related to the elections and identifying the problems with the focus on the 19th Presidential Election. In accordance with the analysis on the data from 128 respondents (53 male and 75 female respondents), the 99.2% (127 respondents) of respondents had informations on elections mainly through broadcasting(77.2%), smart phone(70.9%), Internet(63.8%) and newspapers 32.3% which accounts for 41 respondents) in that sequence. Next, the 87.4% of respondents thought that the informations on elections had more impact on their voting than the generally expected degree. Meanwhile, the voters' awareness on the facts was analyzed by collecting and presenting the information on elections which stated by candidates in the 19th Presidential Election. In accordance with the analysis, there were the significant differences per age groups. The Scheffe test indicated that the respondents in 30s to 40s had significantly higher average awareness than those in 20s. According to the analysis results, it was proposed that the National Election Commission install the election information investigation and analysis committee in the election organization, investigate and analyze the election informations each election for providing real facts to the public, the voters.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.66-85
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• 2020

The purpose of this study is to explain and predict trends the AI development process based on AI technology patents (total) and AI reporting frames in major newspapers. To that end, a summary of South Korean and U.S. technology patents filed over the past nine years and the AI (Artificial Intelligence) news text of major domestic newspapers were analyzed. In this study, Topic Modeling and Time Series Return Analysis using Big Data were used, and additional network agenda correlation and regression analysis techniques were used. First, the results of this study were confirmed in the order of artificial intelligence and algorithm 5G (hot AI technology) in the AI technical patent summary, and in the news report, AI industrial application and data analysis market application were confirmed in the order, indicating the trend of reporting on AI's social culture. Second, as a result of the time series regression analysis, the social and cultural use of AI and the start of industrial application were derived from the rising trend topics. The downward trend was centered on system and hardware technology. Third, QAP analysis using correlation and regression relationship showed a high correlation between AI technology patents and news reporting frames. Through this, AI technology patents and news reporting frames have tended to be socially constructed by the determinants of media discourse in AI development.

• Korean journal of communication and information
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• v.71
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• pp.194-223
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• 2015

This study explores a value chain structure of TV program including news, drama, and comedy. The purpose of this research focused on factor analysis and the relationship among viewer's program selection motivations. This research explores correlation between personal value and viewing motivation. This study was to identify the value structure of respondent on TV program(news, drama, comedy) based on means-end chain theory. The research used structured APT laddering questions and 251 data was analysed. Through such analysis, category difference by stage and relationship difference were identified and hierarchical value map was compared. There are four different value ladders: first is attributes, functional consequences, psychological consequences, and final value. The result shows that on news program the basic function is viewers are want to visual factor and quickly acquire social news and they pursue a value of personal social relationship. Whereas, on drama program, the viewers are reflected by around person, and they selected a program based on closed related person. In addition, the viewers are influenced by program's social nomination, production's brand in drama, and performer's nomination, producer and program prominence on comedy. The program selection is highly correlated on program selection's credibility, vital energetic life, and social relationship. The results shows that there was no significant difference between low involvement group and high involvement group for main category involvement group respondents.

• Journal of Korea Multimedia Society
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• v.12 no.5
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• pp.664-676
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• 2009

As data broadcasting has become available, diverse contents can now be provided through digital TV, IPTV and DMB; yet it is true in the current situation that killer contents are insufficient that can satisfy users. On the contrary, in case of the web, with the advent of web 2.0 aiming at user-centered services, the contents market has grown greatly. The ideas and technologies of Web 2.0, if gratified into data broadcasting, are expected to make a contribution to the vitalization of contents. This paper proposes a method of using RSS, as a concrete example of applying web 2.0 to data broadcasting. Accordingly, we have developed a system for producing data services for the ground wave DMB data broadcasting, by using RSS at the stage of authoring news and the like, for which provision of the latest information is important. And for IPTV, we have developed a data broadcasting application so that users can select the RSS they want, as well as a creation system for using RSS at the authoring stage. It is anticipated that the application of RSS by means of the system will simplify the authoring process, making easy the provision of the latest information through the web, and thereby making possible the provision of diverse services to users.

• Journal of Korea Multimedia Society
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• v.10 no.8
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• pp.1017-1028
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• 2007

In this paper we propose an effective method to represent, store, and retrieve video streams efficiently from a video database. We extract features from each video frame, normalize the feature values, and represent them as values in the range [0,1]. In this way a video frame with f features can be represented by a point in the f-dimensional space $[0,1]^f$, and thus the video stream is represented by a trail of points in the multidimensional space. The video stream is partitioned into video segments based on camera shots, each of which is represented by a trend vector which encapsulates the moving trend of points in a segment. The video stream query is processed depending on the comparison of those trend vectors. We examine our method using a collection of video streams that are composed of sports, news, documentary, and educational videos. Experimental results show that our trend vector representation reduces a reconstruction error remarkably (average 37%) and the retrieval using a trend vector achieves the high precision (average 2.1 times) while maintaining the similar response time and recall rate as existing methods.

• International Commerce and Information Review
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• v.14 no.1
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• pp.391-418
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• 2012

The use of SNS (Social Network Service) has been increasing in world society and the SNS has been used to satisfy different purposes of social groups over the years. In the beginning, the SNS were formed using e-mail, listserve, newsgroup, etc., where information was shared among relatively homogeneous groups of people. Now different groups including corporations have been using SNS such as personal web pages, blogs, Facebook and Twitter for their social media marketing. This study intends to verify the relationship between SNS use and export marketing performance. To achieve this, different types of SNS use were analyzed in order to verify their relationship with export marketing performance. The conceptual model is suggested in this paper and several research constructs are identified. The constructs used in this paper include export marketing performance, SNS use, degree of innovation, product online fitness, marketing competence, and internationalization competence. According to the results, the SNS use directly influences the export marketing performance. In addition, the factors which determine the level of SNS use are product's online fitness and organizational willingness to undertake innovation. Therefore, it is suggested to increase SNS use in different marketing purposes for future research.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.499-510
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• 2020

This study aims to analyze the causes of Internet hate speech, which has recently been emerging as a serious social problem and to seek for countermeasures. The experiences of hate speech are examined through the analysis of college students' essays and the causes and solutions of hate speech are suggested through the in-depth interviews with the experts. College students experience hate speech on the Internet on the basis of attributes such as age, gender, sexual orientation, and regionalism. Online comments on news, social media and online games are the main sources in spreading hate speech. On a personal level the lack of awareness of human dignity and the absence of media education are diagnosed as the reasons for online hate speech. The social reasons for online hate speech lie in the lack of human rights education and the problems of the media. In order to improve the problems of Internet hate speech, various suggestions are proposed on the legal, social and educational levels.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.549-555
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• 2016

This paper tries to find the implications applied to art institutions of Korea by analyzing what the content and consequences of services of the Cleveland Museum of Art provided after the Internet of Things adoption in the theoretical perspectives strengthening service marketing through the Internet of Things increases visits and participation in the museum. For analysis, journal articles, statistics, and government press releases, news articles, web pages, web page articles are collected. The results are first, the application of digital and social media is positive in visit to the museum and monetization. Second, the introduction of the Internet of Things will enhance the museum's 'Education', 'Accessibility', 'Communications' services, as well as significantly increase on and offline participation by activating experience. Third, technical support from related companies with the support of local government funds is essential to build the system. Consequently, in order to enable the participation of the spectators in the galleries it is proposed aggressive adoption of such digital technology in domestic barren market of Internet of Things.

• Journal of Korean Academy of Nursing
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• v.47 no.6
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• pp.806-816
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• 2017

Purpose: As comprehensive nursing care service has gradually expanded, it has become necessary to explore the various opinions about it. The purpose of this study is to explore the large amount of text data regarding comprehensive nursing care service extracted from online news and social media by applying a semantic network analysis. Methods: The web pages of the Korean Nurses Association (KNA) News, major daily newspapers, and Twitter were crawled by searching the keyword 'comprehensive nursing care service' using Python. A morphological analysis was performed using KoNLPy. Nodes on a 'comprehensive nursing care service' cluster were selected, and frequency, edge weight, and degree centrality were calculated and visualized with Gephi for the semantic network. Results: A total of 536 news pages and 464 tweets were analyzed. In the KNA News and major daily newspapers, 'nursing workforce' and 'nursing service' were highly rated in frequency, edge weight, and degree centrality. On Twitter, the most frequent nodes were 'National Health Insurance Service' and 'comprehensive nursing care service hospital.' The nodes with the highest edge weight were 'national health insurance,' 'wards without caregiver presence,' and 'caregiving costs.' 'National Health Insurance Service' was highest in degree centrality. Conclusion: This study provides an example of how to use atypical big data for a nursing issue through semantic network analysis to explore diverse perspectives surrounding the nursing community through various media sources. Applying semantic network analysis to online big data to gather information regarding various nursing issues would help to explore opinions for formulating and implementing nursing policies.