• The Journal of Society for e-Business Studies
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• v.21 no.3
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• pp.79-99
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• 2016

Supply network of automobile part is addressed with the e-invoices generated at real time. Automobile is composed of 8 modules. Firms which produce these modules are defined as the first outsourcing firm. Brake is the part of power control module and so, brake manufacturing firm is called the second outsourcing firm. In this paper, the third supply networks of brake manufacturing firms is analyzed with e-invoices and social network method. At the node-level, the third outsourcing firms are classified into 3 categories, interator, allocator and hub with respect to their role at the ego-network of each brake manufacturing firm. At the network level, A2, one of 3 brake manufacturing firms have more outsourcing firms and bigger centrality than the other brake manufacturing firms. Intre-firms trade patterns are, also, analyzed by using the degree of trade dedication with respect to the modes of business. It is shown that trade pattern of retail, commodity brokerage firm, rubber and plastic manufacturing firm are hierarchical trade because their degree of trade dedication is almost near to 1.

• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.529-537
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• 2014

To establish a foundation to objectively interpret Chosun history, we construct people network of the Chosun dynasty. The network shows scale free network properties as if most social networks do. The people network is composed of 1,379 nodes and 3,874 links and its diameter is 14. To analysis of the network dynamics, whole network that is composed of 27 king networks were constructed by adding the first king, Taejo network to the second king, Jeongjong network and then continuously adding the next king networks. Interestingly, betweenness and closeness centralities were gradually decreased but stress centrality was drastically increased. These results indicate that information flow is gradually slowing and hub node position is more centrally oriented as growing the network. To elucidate key persons from the network, k-core and MCODE algorithms that can extract core or module structures from whole network were employed. It is a possible to obtain new insight and hidden information by analyzing network dynamics. Due to lack of the dynamic interacting data, there is a limit for network dynamic research. In spite of using concise data, this research provides us a possibility that annals of the Chosun dynasty are very useful historical data for analyzing network dynamics.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.105-115
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• 2013

As far as the universities in south Korea are concerned, they have to meet the need of the situation as the number of the incoming students are decreasing because of the population-reducing in south Korea. The Ministry of Education Science and Technology is enforcing the restructuring of an universities by evaluating all the universities in Korea by using some indices (employment rate, supplement rate of students etc.). Most of the universities in Korea are widely permitting the changes of the major study as a method to improve the 'supplement rate of students' among some measures. These changes of major study (moving in and moving out) can give rise to difficulties in managing an university because there might be the departments with a small number of students as they moving out from low level departments to high level ones. Moreover, as raising the change rate of the major study, there is no loss from the university's point of view but a department could be in a difficult situation. The purpose of this study is to grasp the characteristics for changing major study by a general statistical analysis and graphs produced by a social network analysis with the D university's case. The results of this study are as follows; (a) category is from the engineering to humanity-society, (b) entrance level is from low to high, and (c) employment rate is from low to high as well.

• Journal of Environmental Impact Assessment
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• v.31 no.5
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• pp.310-320
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• 2022

This study aimed to identify the change in the public perception of "bats" after the outbreak of the coronavirus (COVID-19) infection. Text mining and network analysis were conducted for blog posts, the largest social network in Korea. We collected 9,241 Naver blog posts from 2019 to 2020 just before the outbreak of COVID-19 in Korea. The data were analyzed with Python and NetMiner 4.3.2, and the public's perception of bats was examined through the relationship of keywords by period. Findings indicated that the frequency of bat keywords in 2020 increased more than 25 times compared to 2019, and the centrality value increased more than three times. The perception of bats changed before and after the outbreak of the pandemic. Prior to COVID-19, bats were highly recognized as a species of wildlife while in the first half of 2020, they were strongly considered as a threat to human society in relation to infectious diseases and health. In the second half of 2020, it was confirmed that the area of interest in bats expanded as the proportion of ecological and cultural types ofresearch increased. This study seeks to contribute to the expansion and direction of future research in bats by understanding the public's interest in the potential impact of the species as disease hosts post the COVID-19 pandemic.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.47-56
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• 2021

The purpose of this study is to use network analysis to identify trends in university personality-related studies and provide implications for future research directions. For the purpose of this study, 194 papers related to personality of university students published in Korean scholarly journals. First, research began to be published in 2004, slightly increased in 2012, continued an upward curve from 2015, peaked in 2017, and is confirmed to be a downward trend. Second, the main keywords with the centrality analysis were 'society' and 'cultivation'. Third, keywords on the cognitive side and individual dimension of personality in the first period (2004 - 2010), social dimension and emotional side of personality in the second period (2011-2015), and social level and cognitive, emotional, and behavioral aspects of personality in the third period (2016-2020). Fourth, Topic 2 consisted of keywords of ability, life, interpersonal, satisfaction, and adaptation, and Topic 1 consisted of competence, morality, citizens, society, and practice. Fifth, Topic 4 alone in the first period, in the order of Topic 1 and Topic 2 in the second period, and in the order of Topic 2 and Topic 1 in the third period.

• Journal of Korean Society of Rural Planning
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• v.27 no.4
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• pp.13-24
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• 2021

This study used big data to analyze visitors' experiences in Fishing Experience Recreation Village. Through the portal site posting data for the past six years, the experience of visiting Fishing Experience Villages in Baekmi and Susan was analyzed. The analysis method used Text mining and Social Network Analysis which are Big data analysis techniques. Data was collected using Textom, and experience keywords were extracted by analyzing the frequency and importance of experience texts. Afterwards, the characteristics of the experience of visiting the Fishing Experience Village were identified through the analysis of the interaction between the experience keywords using 'U cinet 6.0' and 'NetDraw'. First, through TF and TF-IDF values, keywords such as "Gungpyeong Port", "Susan Port", and "Yacht Marina" that refer to the name of the port and the port facilities appeared at the top. This is interpreted as the name of the port has the greatest impact on the recognition of the Fishing Experience Villages, and visitors showed a lot of interest in the port facilities. Second, focusing on the unique elements of port facilities and fishing villages such as "mud flat experience", "fishing village experience", "Gungpyeong port", "Susan port", "yacht marina", and "beach" through the values of degree, closeness, and betweenness centrality interpreted as having an interaction with various experiences. Third, through the CONCOR analysis, it was confirmed that the visitor's experience was focused on the dynamic behavior, the experience program had the greatest influence on the experience of the visitor, and that the experience of the static and the dynamic behavior was relatively balanced. In conclusion, the experience of visitors in the Fishing Experience Villages is most affected by the environment of the fishing village such as the tidal flats and the coast and the fishing village experience program conducted at the fishing port facilities. In particular, it was found that fishing port facilities such as ports and marinas had a high influence on the awareness of the Fishing Experience Villages. Therefore, it is important to actively utilize the scenery and environment unique to fishing villages in order to revitalize the Fishing Experience Villages experience and improve the quality of the visitor experience. This study is significant in that it studied visitors' experiences in fishing village recreation villages using big data and derived the connection between fishing village and fishing village infrastructure in fishing village experience tourism.

• Korean Journal of Culture and Social Issue
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• v.28 no.2
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• pp.133-161
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• 2022

The purpose of this study was to translate and validate the Lesbian, Gay, and Bisexual Identity Scale(LGBIS), which is a scale measuring the multidimensional identities of sexual minorities. For this, we conducted an exploratory factor analysis using a sample of 201 LGBs(homosexuals and bisexuals). Identical to the original scale, eight factors were extracted from the translated scale(i.e., concealment motivation, identity uncertainty, internalized homonegativity, difficult process, acceptance concerns, identity superiority, identity centrality, and identity affirmation), but one item was removed. In addition, the reliability coefficients of the eight factors except for concealment Motivation were satisfactory. The Confirmatory factor analysis revealed that the 8-factor model had a good fit to the data. Finally, to verify the criterion validity, correlation among each eight factor and the scales measuring the identity related scale and the psychological-functioning scale were analyzed. In conclusion, the Korean version of the LGBIS consists of 8 factors and 26 items in total. Also it was found to be a valid measure for LGBS in Korea as well.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.167-181
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• 2023

This study utilized TEXTOM, a social network analysis program to analyze changes in current tourism behavior after travel restrictions were eased after the outbreak of COVID-19. Data on the keywords 'domestic travel' and 'overseas travel' were collected from blogs, cafes, and news provided by Naver, Google, and Daum. The collection period was set from April to December 2022 when social distancing was lifted, and 2019 and 2020 were each set as one year and compared and analyzed with 2022. A total of 80 key words were extracted through text mining and centrality analysis was performed using NetDraw. Finally, through the CONCOR, the correlated keywords were clustered into 4. As a result of the study, tourism behavior in 2022 shows tourism recovery before the outbreak of COVID-19, segmentation of travel based on each person's preferred theme, prioritization of each country's corona mitigation policy, and then selecting a tourist destination. It is expected to provide basic data for the development of tourism marketing strategies and tourism products for the newly emerging tourism ecosystem after COVID-19.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.5
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• pp.10-21
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• 2018

This study used text mining methodology to focus on the perceptions of the landscape embedded in text that users spontaneously uploaded to the "Taean Travel"blogpost. The study area is the Taean Coast National Park. Most of the places that are searched by 'Taean Travel' on the blog were located in the Taean Coast National Park. We conducted a network analysis on the top three places and extracted keywords related to the landscape. Finally, using a centrality and cohesion analysis, we derived landscape perceptions and the major characteristics of those landscapes. As a result of the study, it was possible to identify the main tourist places in Taean, the individual landscape experience, and the landscape perception in specific places. There were three different types of landscape characteristics: atmosphere-related keywords, which appeared in Kkotji Beach, symbolic image-related keywords appeared in Sinduri Coastal Sand Dune, and landscape objects-related appeared in Manlipo Beach. It can be inferred that the characteristics of these three places are perceived differently. Kkotji Beach is recognized as a place to appreciate a view the sunset and is a base for the Taean Coast National Park's trekking course. Sinduri Coastal Sand Dune is recognized as a place with unusual scenery, and is an ecologically valuable space. Finally, Manlipo Beach is adjacent to the Chunlipo Arboretum, which is often visited by tourists, and the beach itself is recognized as a place with an impressive appearance. Social media data is very useful because it can enable analysis of various types of contents that are not from an expert's point of view. In this study, we used social media data to analyze various aspects of how people perceive and enjoy landscapes by integrating various content, such as landscape objects, images, and activities. However, because social media data may be amplified or distorted by users' memories and perceptions, field surveys are needed to verify the results of this study.