• Journal of Korean Library and Information Science Society
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• v.50 no.4
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• pp.77-100
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• 2019

This study aims to analyze and compare centrality and brokerage measures of journal citation network focusing on textmining research. The analytic sample was 193 academic articles collected from 136 KCI journals published in 2018. The journal citation network was constructed based on citation relations. The characteristics, centralities, and brokerages of network was analyzed. The journal citation network consisted 136 nodes and 413 links with directed and weight. According to the five types of centrality(out-degree, in-degree, out-closeness, in-closeness, betweenness), journals of social sciences, engineering, and interdisciplinary research showed higher centrality. Social sciences, engineering and interdisciplinary research journals also showed higher brokerages as a result of brokerage analysis which identify five types of brokerage roles(coordinator, gatekeeper, representative, consultant, liaison). The centralities and brokerages of journals are positively correlated. This study suggested how to construct journal citation network from the articles focusing on certain topics. This was meaningful study in terms of conducting brokerage analysis and comparing it with centrality in the journal citation network.

• Journal of Internet Computing and Services
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• v.13 no.1
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• pp.125-134
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• 2012

As the social networking service (SNS), Facebook, and Cyworld, is developing, the social network game and social business commerce based on this service is activated. Especially, the Social Network Game (SNG) is getting explosive interests and it becomes popular, because it is small scale and user can enjoy the game among close friends. The market for this game is getting larger every year, but still it has some limitations in developing the game. Especially, the current game engine is aiming for developing online or console game, and there is no exclusive game engine for developing SNG. Therefore, it takes lots of time for developing SNG with this game engine. In this paper, we described a design and development of the game engine optimized for developing SNG, which not only adapts the main characteristics of the previous game engine, but also considers the specific characteristics of the SNG. The engine also supports map for the simulation game that is the most popular game in SNG, and also provides modules and tools for developing character animation easily. The evaluation standard for the performance of the game engine is the output generation speed of image, text and character. And the results showed reasonable output speed for developing the SNG in generation of image, text, and character.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.26 no.1
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• pp.217-231
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• 2015

This study aims to infer the gene-protein 'brings_about' chains of pancreatic cancer which were referred to in the pancreatic cancer related researches by constructing the gene-protein interaction network of pancreatic cancer. The chains can help us uncover publicly unknown knowledge that would develop as empirical studies for investigating the cause of pancreatic cancer. In this study, we applied a novel approach that grafts text mining and the main path analysis into Swanson's ABC model for expanding intermediate concepts to multi-levels and extracting the most significant path. We carried out text mining analysis on the full texts of the pancreatic cancer research papers published during the last ten-year period and extracted the gene-protein entities and relations. The 'brings_about' network was established with bio relations represented by bio verbs. We also applied main path analysis to the network. We found the main direct 'brings_about' path of pancreatic cancer which includes 14 nodes and 13 arcs. 9 arcs were confirmed as the actual relations emerged on the related researches while the other 4 arcs were arisen in the network transformation process for main path analysis. We believe that our approach to combining text mining analysis with main path analysis can be a useful tool for inferring undiscovered knowledge in the situation where either a starting or an ending point is unknown.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.5
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• pp.279-284
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• 2017

Currenty, in the era of big data, text mining and opinion mining have been used in many domains, and one of their most important research issues is to extract significant information from social media. Thus in this paper, we propose a logistic regression ensemble method of finding the main body text from blog HTML. First, we extract structural features and text features from blog HTML tags. Then we construct a classification model with logistic regression and ensemble that can decide whether any given tags involve main body text or not. One of our important findings is that the main body text can be found through 'depth' features extracted from HTML tags. In our experiment using diverse topics of blog data collected from the web, our tag classification model achieved 99% in terms of accuracy, and it recalled 80.5% of documents that have tags involving the main body text.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.421-431
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• 2018

The purpose of this study is to analyze the trends of 'traditional' terminology in Korea. We focus on an empirical investigation of how media reports are conveying 'tradition' terminology in our society by applying text mining and social network analysis techniques. The analysis covered 2,481,143 news articles related to 'tradition' terminology that appeared in the media since the 1920's. In this research, frequency analysis, association analysis and social network analysis were used on articles related to 'tradition' terminology from 1920 to 2017 by decade. By applying these data science techniques, we can grasp the meaning of social culture phenomenon related 'tradition' with objective and value-neutral position and understand the social symbolism which contains the tradition of the times.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.11
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• pp.419-426
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• 2018

Due to the FMD(foot-and-mouth disease), the domestic animal husbandry and related industries suffer enormous damage every year. Although various academic researches related to FMD are ongoing, engineering studies on the social effects of FMD are very limited. In this study, we propose a systematic methodology to analyze emotional responses of regular citizens on FMD using text mining techniques. The proposed system first collects data related to FMD from the tweets posted on Twitter, and then performs a polarity classification process using a deep-learning technique. Second, keywords are extracted from the tweet using LDA, which is one of the typical techniques of topic modeling, and a keyword network is constructed from the extracted keywords. Finally, we analyze the various social effects of regular citizens on FMD through keyword network. As a case study, we performed the emotional analysis experiment of regular citizens about FMD from July 2010 to December 2011 in Korea.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.185-199
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• 2018

The purpose of this study is to derive the core technologies of VR using patent analysis and to explore the direction of social and public interest in VR using news analysis. In Study 1, we derived keywords using the frequency of words in patent texts, and we compared by company, year, and technical classification. Netminer, a network analysis program, was used to analyze the IPC codes of patents. In Study 2, we analyzed news articles using T-LAB program. TF-IDF was used as a keyword selection method and chi-square and association index algorithms were used to extract the words most relevant to VR. Through this study, we confirmed that VR is a fusion technology including optics, head mounted display (HMD), data analysis, electric and electronic technology, and found that optical technology is the central technology among the technologies currently being developed. In addition, through news articles, we found that the society and the public are interested in the formation and growth of VR suppliers and markets, and VR should be developed on the basis of user experience.

• Journal of Korea Game Society
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• v.18 no.6
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• pp.69-82
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• 2018

The need of high quality VR contents has been steadily raised in recent years. Therefore, this study investigated the user's interest factors of VR game which is receiving the most attention among VR contents. We used STEAM review data and applied Text mining and Network analysis to perform this research. As a result, it was possible to confirm 4 word clusters related VR game users. Each cluster is named by 'presence', 'first person view game', 'auditory factor' and 'interaction'. This study has its meaning. First, user related research would be very helpful to develop high quality VR game. Second, it confirms that review data of VR game users can be structured, analyzed and used.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.133-145
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• 2022

As a result of the study, the poorest keywords were information, big data, management, policy, government, law, and smart. In addition, as a result of network analysis, related research was being conducted on topics such as data industry policy, data governance performance, defense, governance, and data public. The four topics derived through topic modeling were "DG policy," "DG platform," "DG in laws," and "DG implementation," of which research related to "DG platform" showed an increasing trend, and "DG implementation" tended to shrink. This study comprehensively summarized data governance-related studies. Data governance needs to expand research areas from various perspectives and related fields such as data management and data integration policies at the organizational level, and related technologies. In the future, we can expand the analysis targets for overseas data governance and expect follow-up studies on research directions and policy directions in industries that require data-based future industries such as Industry 4.0, artificial intelligence, and Metaverse.

• 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.