• Journal of the Korean Society for Library and Information Science
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• v.55 no.3
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• pp.103-129
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• 2021

This study examined the characteristics of two keyword types expressing the topics in the intellectual structure analysis based on the co-word analysis, focused on overseas open access field. Specifically, the keyword set extracted from the LISTA database in the field of library and information science was divided into two types (controlled keywords and uncontrolled keywords), and the results of performing intellectual structure analysis based on co-word analysis were compared. As a result, the two keyword types showed significant differences by keyword sets, research maps and influences, and periods. Therefore, in intellectual structure analysis based on co-word analysis, the characteristics of each keyword type should be considered according to the purpose of the study. In other words, it would be more appropriate to use controlled keywords for the purpose of examining the overall research trend in a specific field from the perspective of the entire academic field, and to use uncontrolled keywords for the purpose of identifying detailed trends by research area from the perspective of the specific field. In addition, for a comprehensive intellectual structure analysis that reflects both viewpoints, it can be said that it is most desirable to compare and analyze the results of using controlled keywords and uncontrolled keywords individually.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.3
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• pp.245-256
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• 2022

The purpose of this study is to provide comprehensive insights on the current research trends in entrepreneurship based on topic modeling and keyword co-occurrence analysis. This study queried Web of Science database with 'entrepreneurship' and collected 14,953 research articles between 2002 and 2021. The study used R program for topic modeling and VOSviewer program for keyword co-occurrence analysis. The results of this study are as follows. First, as a result of keyword co-occurrence analysis, 5 clusters divided: entrepreneurship and innovation cluster, entrepreneurship education cluster, social entrepreneurship and sustainability cluster, enterprise performance cluster, and knowledge and technology transfer cluster. Second, as a result of the topic modeling analysis, 12 topics found: start-up environment and economic development, international entrepreneurship, venture capital, government policy and support, social entrepreneurship, management-related issues, regional city planning and development, entrepreneurship research, and entrepreneurial intention. Finally, the study identified two hot topics(venture capital and entrepreneurship intention) and a cold topic(international entrepreneurship). The results of this study are useful to understand current research trends in entrepreneurship research and provide insights into research of entrepreneurship.

• 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 KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.110-114
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• 2010

We describe a new method for text categorization using TextRank algorithm. Text categorization is a problem that over one pre-defined categories are assigned to a text document. TextRank algorithm is a graph-based ranking algorithm. If we consider that each word is a vertex, and co-occurrence of two adjacent words is a edge, we can get a graph from a document. After that, we find important words using TextRank algorithm from the graph and make feature which are pairs of words which are each important word and a word adjacent to the important word. We use classifiers: SVM, Na$\ddot{i}$ve Bayesian classifier, Maximum Entropy Model, and k-NN classifier. We use non-cross-posted version of 20 Newsgroups data set. In consequence, we had an improved performance in whole classifiers, and the result tells that is a possibility of TextRank algorithm in text categorization.

• Journal of the Korean Society for information Management
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• v.30 no.2
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• pp.207-225
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• 2013

Due to the development of science and technology, the convergence of various disciplines has been fostered. Accordingly, interdisciplinary studies have increasingly been expanded by integrating knowledge and methodology from different disciplines. The primary focus of biblimetric methods is on investigating the intellectual structure a field, and analysis of the characterization of interdisciplinary studies is overlooked. In this study, we aim to identify the intellectual structure of the field of medical informatics through author co-citation analysis and co-word analysis by the representative journal "IEEE ENG MED BIOL." In addition, we examine authors and MeSH Terms of top three representative journals for further analysis of the field. We examine the intellectual structure of the medical informatics field by author and word clusters to identify the network structure of medical informatics disciplines.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.3
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• pp.101-118
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• 2014

Given the context of rapid developing ubiquitous computing environment, it is imperative for users to search and use images based on affective meanings. However, it has been difficult to index affective meanings of image since emotions of image are substantially subjective and highly abstract. In addition, utilizing low level features of image for indexing affective meanings of image has been limited for high level concepts of image. To facilitate the access points of affective meanings of image, this study aims to utilize user-provided responses of images. For a data set, emotional words are collected and cleaned from twenty participants with a set of fifteen images, three images for each of basic emotions, love, sad, fear, anger, and happy. A total of 399 unique emotion words are revealed and 1,093 times appeared in this data set. Through co-word analysis and network analysis of emotional words from users' responses, this study demonstrates expanded word sets for five basic emotions. The expanded word sets are characterized with adjective expression and action/behavior expression.

• Proceedings of the Korean Society for Information Management Conference
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• 2013.08a
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• pp.23-26
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• 2013

지식기반사회와 정보홍수시대로 갈수록, 도서관의 존속여부에 대한 고민으로 도서관경영의 중요성은 심화되며, 관련 연구가 많이 이루어지고 있다. 이에 본 연구는 동시출현단어 분석을 통해 도서관경영 분야의 지적구조를 분석하였다. 데이터 수집은 2001~2013년도까지 한국연구재단에 등재된 5개의 문헌정보학 관련 학회지를 대상으로 하였으며, 해당 논문 수는 413건이다. 데이터 처리후 군집분석을 실시하여 9개의 군집을 형성하였으며, 해당 군집은 장서개발, 디지털도서관, 공공도서관, 마케팅 및 조직관리, 국립중앙도서관 및 작은도서관, 인사관리(직무/자격제도), 대학도서관, 학교도서관, 서비스 품질평가이다. 이러한 연구 결과는 기존의 도서관경영 분야의 주제영역과 비교하였다.

• Journal of the Korean Society for information Management
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• v.24 no.4
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• pp.285-303
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• 2007

This study aims to explore a new technique making complementary linkage between controlled vocabularies and uncontrolled vocabularies for analyzing a research domain. Co-word analysis can be largely divided into two based on the types of vocabulary used: controlled and uncontrolled. In the case of using controlled vocabulary, data sparseness and indexer effect are inherent drawbacks. On the other case, word selection by the author's perspective and word ambiguity. To complement each other, we suggest a descriptor profiling that represents descriptors(controlled vocabulary) as the co-occurrence with words from the text(uncontrolled vocabulary). Applying the profiling to the domain of information science implies that this method can complement each other by reducing the inherent shortcoming of the controlled and uncontrolled vocabulary.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.1
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• pp.207-228
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• 2013

Due to the advance of scholarly communication, the field of open access has been studied over the last decade. The purpose of this study is to analyze and demonstrate the field of open access via co-word analysis. The data set was collected from Web of Science citation database during the period from January 1998 to July 2012 using the Topic category. A total of 479 journal articles were retrieved and 8,643 noun keywords were extracted from the titles and abstracts. In order to achieve the purpose of this study, network analysis, clustering analysis and multidimensional scaling mapping were used to examine the domain and the sub-domains of open access field. 18 clusters in the network analysis are recognized and 4 clusters are shown in the map of multidimensional scaling. In addition, the centrality analysis in the weighted networks was used to explore the significant keywords in this field. The results of this study are expected to demonstrate and guide the intellectual structure and new approaches of open access field.

• Korean Journal of Environment and Ecology
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• v.33 no.1
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• pp.9-15
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• 2019

Artiodactyla, which is an even-toed mammal, widely inhabits worldwide. In recent years, wild Artiodactyla species have attracted public attention due to the rapid increase of crop damage and road-kill caused by wild Artiodactyla such as water deer and wild boar and the decrease of some species such as long-tailed goral and musk deer. In spite of such public attention, however, there have been few studies on Artiodactyla in Korea, and no studies have focused on the trend analysis of Artiodactyla, making it difficult to understand actual problems. Many recent studies on trend used text-mining and co-occurrence analysis to increase objectivity in the classification of research subjects by extracting keywords appearing in literature and quantifying relevance between words. In this study, we analyzed texts from research articles of three countries (Korea, China, and Japan) through text-mining and co-occurrence analysis and compared the research subjects in each country. We extracted 199 words from 665 articles related to Artiodactyla of three countries through text-mining. Three word-clusters were formed as a result of co-occurrence analysis on extracted words. We determined that cluster1 was related to "habitat condition and ecology", cluster2 was related to "disease" and cluster3 was related to "conservation genetics and molecular ecology". The results of comparing the rates of occurrence of each word clusters in each country showed that they were relatively even in China and Japan whereas Korea had a prevailing rate (69%) of cluster2 related to "disease". In the regression analysis on the number of words per year in each cluster, the number of words in both China and Japan increased evenly by year in each cluster while the rate of increase of cluster2 was five times more than the other clusters in Korea. The results indicate that Korean researches on Artiodactyla tended to focus on diseases more than those in China and Japan, and few researchers considered other subjects including habitat characteristics, behavior and molecular ecology. In order to control the damage caused by Artiodactyla and to establish a reasonable policy for the protection of endangered species, it is necessary to accumulate basic ecological data by conducting researches on wild Artiodactyla more.