• Journal of Information Science Theory and Practice
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• v.10 no.4
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• pp.53-65
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• 2022

Altmetrics or alternative metrics gauge the digital attention received by scientific outputs from the web, which is treated as a supplement to traditional citation metrics. In this study, we performed a meta-analysis of correlations between classic citation metrics and altmetrics indicators of library and information science (LIS) articles. We followed the systematic review method to select the articles and Erasmus Rotterdam Institute of Management Guidelines for reporting the meta-analysis results. To select the articles, keyword searches were conducted on Google Scholar, Scopus, and ResearchGate during the last week of November 2021. Eleven articles were assessed, and eight were subjected to meta-analysis following the inclusion and exclusion criteria. The findings reported negative and positive associations between citations and altmetric indicators among the selected articles, with varying correlation coefficient values from -.189 to 0.93. The result of the meta-analysis reported a pooled correlation coefficient of 0.47 (95% confidence interval, 0.339 to 0.586) for the articles. Sub-group analysis based on the citation source revealed that articles indexed on the Web of Science showed a higher pooled correlation coefficient (0.41) than articles indexed in Google Scholar (0.30). The study concluded that the pooled correlation between citation metrics with altmetric indicators was positive, ranging from low to moderate. The result of the study gives more insights to the scientometrics community to propose and use altmetric indicators as a proxy for traditional citation indicators for quick research impact evaluation of LIS articles.

• Korean Journal of Construction Engineering and Management
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• v.22 no.1
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• pp.13-26
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• 2021

To promote the off-site construction (OSC) in Korea, technical innovation applied to each phase, such as design, engineering, factory production, and site assembly, is important and equally necessary is the development of management and operation methods that are different from existing construction production methods. However, the current OSC-related studies in Korea are conducted from the technical development viewpoints, such as construction methods. Additionally, few studies have been conducted to derive a management measure for successful OSC projects. Therefore, studies to derive a management measure based on a clear understanding of the core success factors of OSC projects are required. This study aims to analyze several studies related to the success factors of OSC projects conducted overseas and to show its core implications for the successful management of OSC projects in Korea. We expect this study to improve the viability of OSC projects, which will be expanded in Korea in the future.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1137-1144
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• 2020

This paper aims to provide strategic suggestions by analyzing technology trends related to big data, IoT, and artificial intelligence. To this end, analysis was performed using the 2018 national R&D information, and major basic analysis and language network analysis were performed. As a result of the analysis, research and development related to big data, IoT, and artificial intelligence are being conducted by focusing on the basic and development stages, and it was found that universities and SMEs have a high proportion. In addition, as a result of the language network analysis, it is judged that the related fields are mainly research for use in the smart farm and healthcare fields. Based on these research results, first, big data is essential to use artificial intelligence, and personal identification research should be conducted more actively. Second, they argued that full-cycle support is needed for technology commercialization, not simple R&D activities, and the need to expand application fields.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.1-7
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• 2021

Investor mood from social media is gaining increasing attention for leading a price movement in stock market. Based on the behavioral finance theory, this study argues that sentiment extracted from social media using big data technique can predict a real-time (short-run) price momentum in Chinese stock market. Collecting Sina Weibo posts that related to COVID-19 using keyword method, a daily influential weighted sentiment factors is extracted from the sizable raw data of over 2 millions of posts. We examine one supervised and 4 unsupervised sentiment analysis model, and use the best performed word-frequency and BiLSTM mdoel. The test result shows a similar movement between stock price change and sentiment factor. It indicates that public mood extracted from social media can in some extent represent the investors' sentiment and make a difference in stock market fluctuation when people are concentrating on a special events that can cause effect on the stock market.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.261-270
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• 2020

In this study, we identify promising technologies for Piggyback transportation system by analyzing the relevant patent information. In order for this, we first develop the patent database by extracting relevant technology keywords from the pioneering research papers for the Piggyback flactcar system. We then employed textmining to identify the frequently referred words from the patent database, and using these words, we applied the LDA (Latent Dirichlet Allocation) algorithm in order to identify "topics" that are corresponding to "key" technologies for the Piggyback system. Finally, we employ the ARIMA model to forecast the trends of these "key" technologies for technology forecasting, and identify the promising technologies for the Piggyback system. with keyword search method the patent analysis. The results show that data-driven integrated management system, operation planning system and special cargo (especially fluid and gas) handling/storage technologies are identified to be the "key" promising technolgies for the future of the Piggyback system, and data reception/analysis techniques must be developed in order to improve the system performance. The proposed procedure and analysis method provides useful insights to develop the R&D strategy and the technology roadmap for the Piggyback system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.999-1005
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• 2020

While search portals' 'Portal News' account for the largest portion of aggregated news outlet, its neutrality as an outlet is questionable. This is because news aggregation may lead to prejudiced information consumption by recommending biased news articles. In this paper we introduce a new method of measuring political bias of news articles by using deep learning. It can provide its readers with insights on critical thinking. For this method, we build the dataset for deep learning by analyzing articles' bias from keywords, sourced from the National Assembly proceedings, and assigning bias to said keywords. Based on these data, news article bias is calculated by applying deep learning with a combination of Convolution Neural Network and Recurrent Neural Network. Using this method, 95.6% of sentences are correctly distinguished as either conservative or progressive-biased; on the entire article, the accuracy is 46.0%. This enables analyzing any articles' bias between conservative and progressive unlike previous methods that were limited on article subjects.

• Journal of Korean Library and Information Science Society
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• v.52 no.1
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• pp.55-77
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• 2021

Based on the analysis of historical backgrounds and terms of Taekwondo, this study was conducted to analyze the characteristics of cataloging records related to Taekwondo in 53 national libraries of each country. The results are as follows. To begin with, while most of the Taekwondo-related records are concentrated in some specific national libraries such as the United States, Germany, Republic of China, United Kingdom, and Spain, there are four libraries that do not have one. Second, the title keyword of Taekwondo-related records was 93.5% for the term that directly meant Taekwondo and 6.5% for Korean martial art, Korean art of self-defense, and Korean karate etc. The frequency of materials by language is 38.7% for English and 8~9% for German, Spanish, Chinese, and Korean, respectively. The Roman translation for Taekwondo is 50.3% for 'Taekwondo', and 18.5% for 'Tae kwon do'. Third, the subject heading of Taekwondo-related records was 86.9% for 'Tae kwon do' or 'Taekwondo' etc. 7.6% for 'karate', 5.7% for general subject heading, and 12.0% for blank. This means that some national libraries misunderstand Taekwondo as karate.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.662-674
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• 2021

Metabolic syndrome is closely associated with cardiovascular disease, there is increasing attentions in prevention of metabolic syndrome through prediction. The aim of this study was to systematically review the literature by collecting, analyzing, and synthesizing articles of predicting metabolic syndrome in Koreans. For systemic review, data search was conducted on Global journals Pubmed, WoS and domestic journals DBPia, KISS published in 2011-2020 year. Three keyword 'Metabolic syndrome', 'predict', and 'korea' were used for searching under AND condition. Total 560 articles were searched and the final 22 articles were selected according to the data selection criteria. The most useful variable was WHtR(AUC=0.897), most frequently used analysis method was logistic regression(63.6%), and most accurate analysis method was XGBOOST(AUC=0.879) for predicting metabolic syndrome. Prediction accuracy was slightly improved when sasang constitution types was used. Based on the results of this study, it is believed that various large-scale longitudinal studies for the prediction and management of the Metabolic syndrome in Korean should be followed in the future.

• The Korean Journal of Franchise Management
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• v.13 no.4
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• pp.1-12
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• 2022

Purpose: In 2020, the franchise industry accomplished a significant growth compared to the previous year, as the number of franchise companies increased by 9.0% while the number of franchise brands increased by 12.5%. Despite growth in size, the Korean franchise industry underwent many negative incidents, such as franchise ownership sales to private equity funds, that led to deterioration of businesses. From this point of view, this study aims to make various proposals to help policy makers develop franchise industry policies by analyzing trends of the current and previous presidential administrations' franchise policies and regulations using newspaper articles. Research design, data and methodology: A total of 7,439 articles registered in Naver API from February 25, 2013 to November 29, 2021 were extracted. Among them, 34 unrelated video articles were deleted, and a total of 7,405 articles from both administrations were used for analysis. The R package was used for word frequency analysis, word clouding, word correlation analysis, and LDA (Latent Dirichlet Allocation) topic modeling. Results: The keyword frequency analysis shows that the most frequently mentioned keywords during the previous administration include 'no-brand', 'major company', 'bill', 'business field', and 'SMEs', and those mentioned during the current administration include 'industry' and 'policy'. As a result of LDA topic modeling, 9 topics such as 'global startups' and 'job creation' from the previous administration, and 10 topics such as 'franchise business' and 'distribution industry' from the current administration were derived. The results of LDAvis showed that the previous administration operated a policy based on mutual growth of large and small businesses rather than hostile regulations in the franchise business, whereas the current administration extended the regulation related to franchise business to the employment sector. Conclusions: The analysis of past two administrations' franchise policy, it can be suggested that franchisors and franchisees may complement each other in developing the Fair Transactions in Franchise Business Act and achieving balanced growth. Moreover, political support is needed for sound development of franchisors. Limitations and future research suggestions are presented at the end of this study.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.468-475
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• 2022

The purpose of this study is to identify trends in domestic breaking research to derive characteristics and implications, and further suggest future research directions. To this end, literature analysis (the timing of paper publication, research method, research topic) and keyword analysis of 50 papers related to breaking published in academic journals registered with the Korea Research Foundation (KCI) were conducted. The research results are as follows. First, the trend by thesis publication period was first published in 2006, showed a slight increase in 2012, and then increased rapidly in 2021. Second, domestic braking-related research has been mainly focused on qualitative research (60%). Third, looking at the research topic, it is divided into three categories: identity establishment, culture and arts field, and sports field, of which studies related to identity establishment accounted for more than 60%. Finally, looking at the keywords frequently used in breaking papers, the most frequently appeared word was 'hip-hop', followed by 'culture'. Based on these results, implications were drawn to establishing the identity of braking through academic and theoretical approaches, practical approaches through the development of standardized textbooks and curriculum, strengthening the characteristics and capabilities of the field through integrated approaches, and changing to sports.