• The Journal of the Korea Contents Association
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• v.19 no.11
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• pp.102-110
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• 2019

The military respond well to external publics in the event of a crisis int that they are operated based on the trust of the people. Unlike other organizations, however, the Korean military has the distinctiveness that soldiers experience military life as internal publics for a certain period of time and after serving in the army, they become those who evaluate the military as external publics. Therefore, it is important to examine what would be effective crisis management strategies in terms of communicating with active-duty soldiers. Given that active-duty soldiers are accustomed to using SNS these days, this study investigated whether message forms (digital image vs. text) affect the perception of the military in crisis, acceptance of the given message, and attitude toward the military. Our empirical findings suggest that image-based messages are more likely to increase levels of message acceptance than text-based messages. Based on the results, we discussed practical implications on communication strategies for managing the military in crisis.

• Journal of Korean Library and Information Science Society
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• v.51 no.3
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• pp.251-279
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• 2020

This study noted the recent impact of Coronavirus Disease-19 (Corona 19) on the environment surrounding the library, and investigated the libraries' response activities. In addition, related issues on news media and social media were detected based on text mining techniques to engage environmental changes surrounding the library. Key issues were derived from 1,852 news reports on the library related to the Corona 19 situation and 227,983 tweets related to the library during the Corona 19 epidemic. Through this, implications were derived: prolonged 'Untact' situations, increased e-book lending, improved expectations for online services and librarians, and re-conceptualized library space. In addition, the direction of future services was discussed by selecting representative examples of library services provided in the non-face-to-face (untact) situation and dividing them into books, services, and spaces.

• The Journal of the Korea Contents Association
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• v.13 no.4
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• pp.427-439
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• 2013

With the fast development of complex science, lots of social networks are studied. We know that the social network is widely applied in analyzing issues in human culture, economics and web sciences. Recently we witness that some researchers began to compare the social network constructed from fiction literatures(literature social network) and the real social network obtained from practice. But we point that previous approaches for literature social network have some drawbacks since they completely depend on the biographical dictionary constructed for a designated literature. So since the previous approach focus on the few important characters and peoples around them, we can not understand the global structure of all characters appeared in the literature at least once. We propose one method to extract all characters appeared in the literature and how to make the social network from that information. Also we newly propose K-critical network by applying frequency of the named characters and the strength of relationship among all textual characters. Our experiment shows that the K-critical measure could be one crucial quantitative measure to compute the relationship strength among characters appeared in the object literature.

• The Journal of the Convergence on Culture Technology
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• v.2 no.2
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• pp.29-35
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• 2016

The conventional educational robots, which are commonly industrial robots or toy robots, use text-based programming to teach the students. Therefore, students have difficulty in studying robotics due to the difficulties of text based language. The developed robot in this study have a camera, which have the color tracking function, and it has various sensors and actuators. It supports the open hardware and uses graphic language based programming. The developed educational robot is programmed by Scratch, which uses graphic modular language. We also present a curriculum, which is based upon the developed robot and Scratch. We applied the robot and curriculum to the primary school students. We obtained satisfactory results comparing it with the conventional robot education. Furthermore, the imagination and execution ability of students showed enhancement in learning robotics. Thus, this fact means the validity and effectiveness of the proposed approach.

• Journal of Digital Convergence
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• v.12 no.5
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• pp.57-68
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• 2014

This article analyses frame transition of personal information leakage in Korea from 1984 to 2014. In order to investigate the transition, we have collected newspaper article's titles. This study adopts classification, text network analysis(by co-occurrence symmetric matrix), and clustering techniques as part of social network analysis. Moreover, we apply definition of centrality in network in order to reveal the main frame formed in each of four periods. As a result, accessibility of personal information is extended from public sector to private sector. The boundary of personal information leakage is expanded to overseas. Therefore it is urgent to institutionalize the protection of personal information from a global perspective.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.61-77
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• 2017

Recently, the number of academic conference information on the Internet has rapidly increased, the automatic classification of academic conference information according to research subjects enables researchers to find the related academic conference efficiently. Information provided by most conference listing services is limited to title, date, location, and website URL. However, among these features, the only feature containing topical words is title, which causes information insufficiency problem. Therefore, we propose methods that aim to resolve information insufficiency problem by utilizing web contents. Specifically, the proposed methods the extract main contents from a HTML document collected by using a website URL. Based on the similarity between the title of a conference and its main contents, the topical keywords are selected to enforce the important keywords among the main contents. The experiment results conducted by using a real-world dataset showed that the use of additional information extracted from the conference websites is successful in improving the conference classification performances. We plan to further improve the accuracy of conference classification by considering the structure of websites.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.239-252
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• 2020

By using text mining, we explore the factors responsible for an increase in SUV preference. We collected 32,679 posts related to SUVs from "Bobaedream," the largest online automobile community in South Korea, and applied the LDA topic model. While previous studies have explained the SUV boom as an individual's risk aversion strategy from crime, the result shows that the topic of 'Safety' appears to be an important factor in the SUV discourse in the context of a car accident and high-speed driving situation. To conclude, the consumption of SUVs in Korean society serves as a mean to prevent anxiety and danger to individuals when driving. We insist that decreasing social trust, caused by an increase in inequality, underlies the perception of risk on the road.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.31-37
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• 2020

This study examines the way poetry text is inserted in dramas and the way poets represent themselves through the drama "The climax" (2011). The drama features Lee Yuk-sa, a poet and independence activist, as a central figure and chooses a narrative structure that follows his life. The drama maximizes the lyricity and visual beauty of the drama by inserting his poems with fantastic images at the most dramatic moments of the poet's life. The image presented with the poem maximizes Lee Yuk-sa's intense hardship, while portraying the poem as a crystal of this hardship. Thus, the drama "The climax" uses Lee Yuk-sa's poetry to visualize the inner world of the central character Lee Yuk-sa. Lee Yuk-sa's poems are used in conjunction with his image to simultaneously represent the beauty of poetry and the upright spirit of the poet. This is the result of a balanced portrayal of Yi Yuk-sa, a poet and independence activist, as an intellectual who acts. The drama "The climax" is the main text that sincerely performed the representations of poems and poets through video.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.550-555
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• 2018

This study aims to identify and compare contents and keywords used in articles related to blockchain applications to various industries. The text mining and Semantic Network Analysis, as methods of keyword network analysis, were used to analyze articles including terms of 'finance' 'energy' and 'logistics', which media and government frequently mentioned as areas that can apply blockchain technologies. For this study, data were collected from 43,093 articles from January, 2017 through July, 2018. Data crawling was carried out by using Python BeautifulSoup and data cleaning was performed in order to eliminate mutual redundancies of the three terms. After that, text mining and semantic network analysis were performed using Textom and UCInet for network analysis between keywords. The results showed that all the three terms were similar in terms of 'technology', but there were differences in the contents of 'government policy' or 'industry' issues. In addition, there were differences in frequencies and centralities of these terms.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.255-263
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• 2015

In this paper, we suggest a plan to take advantage of the SNS data to proactively identify the information on crime risk factor and to prevent crime. Recently, SNS(Social Network Service) data have been used to build a proactive prevention system in a variety of fields. However, when users are collecting SNS data with simple keyword, the result is contain a large amount of unrelated data. It may possibly accuracy decreases and lead to confusion in the data analysis. So we present a method that can be efficiently extracted by improving the search accuracy through text mining analysis of SNS data.