• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.431-453
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• 2022

Hate is a collective expression of exclusivity toward others and it is fostered and reproduced through false public perception. This study aims to explore the objects and issues of hate discussed in our society using text mining techniques. To this end, we collected 17,867 news data published from 1990 to 2020 and constructed a co-word network and cluster analysis. In order to derive an explicit co-word network highly related to hate, we carried out sentence split and extracted a total of 52,520 sentences containing the words 'hate', 'prejudice' and 'discrimination' in the preprocessing phase. As a result of analyzing the frequency of words in the collected news data, the subjects that appeared most frequently in relation to hate in our society were women, race, and sexual minorities, and the related issues were related laws and crimes. As a result of cluster analysis based on the co-word network, we found a total of six hate-related clusters. The largest cluster was 'genderphobic', accounting for 41.4% of the total, followed by 'sexual minority hatred' at 28.7%, 'racial hatred' at 15.1%, 'selective hatred' at 8.5%, 'political hatred' accounted for 5.7% and 'environmental hatred' accounted for 0.3%. In the discussion, we comprehensively extracted all specific hate target names from the collected news data, which were not specifically revealed as a result of the cluster analysis.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.159-170
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• 2021

The purpose of this study was to understand the knowledge structure through keyword network analysis for the purpose of identifying research trends in the research field of multicultural education. To this end, the research trends and intellectual structure of multicultural education were identified through network analysis of words that appeared more than 6 times in the keywords of the papers registered in the KCI (Korean Journal of Citation Index) from 2002 to 2020. Study changes were analyzed by analysis. As a result of the analysis, the first period (2002-2010) focused on multicultural society and multiculturalism, while the second period (2011-2015) additionally introduced multicultural families, globalization, and teacher education, and the third period (2016-2020), multicultural receptivity, multicultural sensitivity, and multicultural efficacy were newly revealed. The research trend of multicultural education in Korean society over the past 19 years has been confirmed that the research topic has changed from theoretical research to empirical research, and the content of multicultural education has also been specified and expanded by field and subject.

• Journal of the Korean Society of Safety
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• v.38 no.4
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• pp.23-31
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• 2023

Revising the Occupational Safety and Health Act led to enacting and revising related laws and systems, such as placing fire observers in hot workplaces. However, the operating standards in such cases are still ambiguous. Although fire accidents occur through multiple and multi-step factors, the hazards of fire accidents have been identified in this study as individual rather than interrelated factors. The aim has been to identify multiple factors of accidents, outlining fire and explosion accidents that recently occurred in the domestic manufacturing industry. First, major keywords were extracted through text mining. Then representative accident types were derived by combining the main keywords through the co-word network analysis to identify the hazards and their relationships. The representative fire accidents were identified as six types, and their major hazards were then addressed for improving safety measures using the identification of hazards in the "Risk Assessment" tool. It is found that various safety measures, such as professional fire observers' training and clear placement standards, are needed. This study will provide useful basic data for revising practical laws and guidelines for fire accident prevention, system supplementation, safety policy establishment, and future related research.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.393-413
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• 2021

Digital humanities, which creates new and innovative knowledge through the combination of digital information technology and humanities research problems, can be seen as a representative multidisciplinary field of study. To investigate the intellectual structure of the digital humanities field, a network analysis of authors and keywords co-word was performed on a total of 441 papers in the last two years (2019, 2020) at the Digital Humanities Conference. As the results of the author and keyword analysis show, we can find out the active activities of Europe, North America, and Japanese and Chinese authors in East Asia. Through the co-author network, 11 dis-connected sub-networks are identified, which can be seen as a result of closed co-authoring activities. Through keyword analysis, 16 sub-subject areas are identified, which are machine learning, pedagogy, metadata, topic modeling, stylometry, cultural heritage, network, digital archive, natural language processing, digital library, twitter, drama, big data, neural network, virtual reality, and ethics. This results imply that a diver variety of digital information technologies are playing a major role in the digital humanities. In addition, keywords with high frequency can be classified into humanities-based keywords, digital information technology-based keywords, and convergence keywords. The dynamics of the growth and development of digital humanities can represented in these combinations of keywords.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.153-171
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• 2017

Many readers tend to read books of a specific author and to expand their reading areas according to the author. This study chose Edgar Allan Poe and analyzed the image of the author using co-recommended authors and books by other readers. The frequencies of co-occurred authors and books were investigated and the relations of authors and books were analyzed with network analysis methods. As a result, genre images of Poe, related authors, and related books are discovered. This study also suggested the methods to identify the image of a author, related author groups, and related books for libraries' reading programs and book curation.

• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.3
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• pp.109-119
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• 2019

The purpose of this study is to examine fashion trends and the direction of the four fashion collections by analyzing the design key-words of the four major international fashion collections in 2018. The data of this study was collected by extracting the key-words from Marie Claire Korea in 2018, with the total of the collected data numbering 2,144. The data was analyzed by text mining using the R program and word-cloud, and a co-occurrence network analysis was conducted. The results of this study are as follows: First, the key-words of fashion collection designs in 2018 were fringe and ruffle detail, silk and denim fabric, vivid color, stripe and check pattern, pants suit item, and oversized silhouette, focusing on romanticism and sport. Second, seasonal characteristics of the fashion collections were pastel colors in S/S, primary and vivid colors in F/W. Details were embroidery and cutouts in S/S, patchwork and fringe in F/W. Third, the design trends of the four major fashion collections were presented in the Paris collection: stripes, check patterns, embroidery, lace, tailoring, draping, romanticism, and glamor. In the Milan collection, checks, prints, denim, and minidresses reflected sport and romanticism. The London collection included fringe, ruffles, floral patterns, flower patterns, and romanticism. The New York collections included vivid colors, neon colors, pastel colors, oversize silhouettes, bodysuits, and long dresses.

• 한국체육학회지인문사회과학편
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• v.57 no.2
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• pp.279-289
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• 2018

The purpose of this study is to investigate features of leisure and recreation scholarship study in The Korean Journal of physical education based on co-authors network and topic modeling through using Word Cloud and LDA Topic Modeling(Latent Dirichlet Allocation). The data collected for this study are 2,697 papers published online from January 2008 to March 2017 on the Korean journal of physical education. Respectively ordered analysis targets are the major author, author of correspondence, co-author 1, co-author 2, co-author n in related document to explore studies' trends using the 369 documents. As a result, the co-author network analysis result found that 451 were linked to the research network, on average researchers had 1.52 relationships and the average distance between researchers was 2.33. The Representative author's concentration of connection was ranked high in the order of the following, Lee. K. M., Hwang. S. H., H., Lee. C. S., and proximity centers were shown in Seo K. B., Han. J. H., Kim. K. J. Finally, parameter-centric features appeared in order of Lee. C. W. and Seo. K. B. was most actively connected between the researchers of the leisure-related academic papers. Future research needs discussions among scholars regarding the trend and direction of future leisure research.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.239-259
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• 2022

Since 2019, research on microplastics has been actively conducted around the world, so analyzing the differences between domestic and foreign microplastics research can be a milestone in establishing the direction of domestic research. In this study, microplastic papers from KCI and WoS were extracted and the differences between domestic and foreign studies were analyzed using a network analysis methodology based on big data such as author keyword co-occurrence word analysis, thesis co-citation analysis, and author co-citation analysis. As a result of the analysis, the analysis of the research topic confirmed that studies that could affect the human body and the treatment of microplastics in daily life were additionally needed in Korea. In the analysis of the depth of thesis citation that examines the quality of research, it was found that Korea was still insufficient at 2.25 overseas and 1.39 in Korea. In the analysis of the composition of the joint research front, where various researchers participate and share information, 3 out of 22 clusters in Korea are Star type. In the case of overseas, all 19 clusters have a mesh structure, so it was confirmed that information flow and sharing were insufficient in specific research fields in Korea. These research results confirmed the need to expand the research topic of microplastics, improve the quality of research, and improve the research promotion system in which various researchers participate. In addition, if the automation program is developed based on topic modeling, it will be possible to build a system capable of real-time analysis.

• Journal of the Korean Society for information Management
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• v.33 no.3
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• pp.63-83
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• 2016

As the usage of information resources produced in various media and forms has been increased, the importance of metadata as a tool of information organization to describe the information resources becomes increasingly crucial. The purposes of this study are to analyze and to demonstrate the intellectual structure in the field of metadata through co-word analysis. The data set was collected from the journals which were registered in the Core collection of Web of Science citation database during the period from January 1, 1998 to July 8, 2016. Among them, the bibliographic data from 727 journals was collected using Topic category search with the query word 'metadata'. From 727 journal articles, 410 journals with author keywords were selected and after data preprocessing, 1,137 author keywords were extracted. Finally, a total of 37 final keywords which had more than 6 frequency were selected for analysis. In order to demonstrate the intellectual structure of metadata field, network analysis was conducted. As a result, 2 domains and 9 clusters were derived, and intellectual relations among keywords from metadata field were visualized, and proposed keywords with high global centrality and local centrality. Six clusters from cluster analysis were shown in the map of multidimensional scaling, and the knowledge structure was proposed based on the correlations among each keywords. The results of this study are expected to help to understand the intellectual structure of metadata field through visualization and to guide directions in new approaches of metadata related studies.

• ETRI Journal
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• v.45 no.1
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• pp.93-104
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• 2023

Coreference resolution is a task in discourse analysis that links several headwords used in any document object. We suggest pointer networks-based coreference resolution for Korean using multi-task learning (MTL) with an attention mechanism for a hierarchical structure. As Korean is a head-final language, the head can easily be found. Our model learns the distribution by referring to the same entity position and utilizes a pointer network to conduct coreference resolution depending on the input headword. As the input is a document, the input sequence is very long. Thus, the core idea is to learn the word- and sentence-level distributions in parallel with MTL, while using a shared representation to address the long sequence problem. The suggested technique is used to generate word representations for Korean based on contextual information using pre-trained language models for Korean. In the same experimental conditions, our model performed roughly 1.8% better on CoNLL F1 than previous research without hierarchical structure.