• 한국벤처창업학회:학술대회논문집
• /
• 2020.06a
• /
• pp.31-37
• /
• 2020

높은 위험을 안고 사업을 하는 벤처 기업은 자금 조달이 쉽지 않다. 벤처 캐피탈은 벤처의 재정적 필요를 해결하고 부족한 역량을 보충함으로써 벤처의 성공을 돕고 고위험 고수익의 벤처 생태계를 지탱하는 중요한 역할을 담당한다. 국내 벤처 캐피탈의 성장과 지속적인 관심에도 불구하고 학문적 성과가 충분히 축적되고 있는지는 의문이다. 이에 따라 본 연구는 2011년부터 2019년까지 벤처창업을 주제로 한 연구의 주요 흐름을 텍스트 마이닝 방법을 통해 고찰함으로써 문제를 진단하고 시사점을 도출하고자 한다. KCI 키워드 트렌드와 벤처 캐피탈의 성장에 관한 시계열 상관분석의 결과 학술적 성과가 벤처 캐피탈의 성장 추이를 따라가지 못하는 것으로 보인다. 또한 벤처창업연구의 주제 흐름을 바이그램과 TF-IDF로 관찰한 결과 2016 이후 창업 기업에 대한 연구 관심이 두드러지고 2019년에 들어 벤처 캐피탈에 관한 연구 커뮤니티의 관심이 높아진 것으로 나타났다. 본 연구의 결과는 벤처 캐피탈에 관한 주요 연구 토픽을 보다 더 적극적으로 발굴하고 탐구함으로써 연구 커뮤니티의 책무를 강화하고 한국의 벤처 캐피탈 성장과 그에 따른 이슈들을 논의할 이론적 기틀 마련이 필요함을 환기한다.

• Journal of the Korea Society for Simulation
• /
• v.25 no.3
• /
• pp.107-116
• /
• 2016

The recent diversification in terms of the scope and techniques used for simulations has highlighted the importance of analyzing state of the art trends and applying these for educational and study purposes. While qualitative methods such as literature research or experts' assessments have previously been used, such methods are in fact likely to reflect the subjective viewpoint of experts, and to involve too much time and money for the results obtained. For the purpose of an objective analysis, a quantitative analysis that included the examination of topics found in domestic academic journal articles was conducted in the present study. In this regard, simulation was found to be most actively used domestically in the electrical and electronic fields. In addition, simulation was also found to be employed for the purpose of education and entertainment in the social sciences. The results of this study are expected to help to facilitate the prediction of the direction of the development of not only the Korea Society for Simulation, but also domestic simulation studies. This study also raises the possibility of applying text mining to trend analysis, and proves that it can be a useful method for deriving future key topics and helping experts' decisions regarding quantitative data.

• Journal of Industrial Convergence
• /
• v.19 no.6
• /
• pp.11-19
• /
• 2021

The purpose of this study is to explore trends in research at home and abroad related to "Sport Facilities", and seek the direction of further research. 1,801 abstracts of papers including "Sport Facilities" were collected from the SCOPUS DB from 2016 to 2020. Topic modeling techniques based on Latent Dirichlet Allocation (LDA) algorithm implemented in R language, TD-IDF techniques, and word cluds using Tagxedo was conducted to analyze the data. As a result, 8 topics were optimally determined, and "sports", "facilities", "health", "physical", "data", and "using" were derived as the main keywords for topics. This results indicated that studies on physical activity, health and using facilities regarding sports facilities at home and abroad have been actively carried out in recent years. This indicates that papers in SCOPUS DB are paying attention to the instrumental value of sport facilities, such as health promotion and improving the quality of life. Therefore, various studies that help participants who use sport facilities for a healthy life should be continuously conducted in the future.

• Journal of Internet Computing and Services
• /
• v.16 no.2
• /
• pp.57-66
• /
• 2015

Considerable research efforts are being directed towards analyzing unstructured data such as text files and log files using commercial and noncommercial analytical tools. In particular, researchers are trying to extract meaningful knowledge through text mining in not only business but also many other areas such as politics, economics, and cultural studies. For instance, several studies have examined national pending issues by analyzing large volumes of text on various social issues. However, it is difficult to provide successful information services that can identify R&D documents on specific national pending issues. While users may specify certain keywords relating to national pending issues, they usually fail to retrieve appropriate R&D information primarily due to discrepancies between these terms and the corresponding terms actually used in the R&D documents. Thus, we need an intermediate logic to overcome these discrepancies, also to identify and package appropriate R&D information on specific national pending issues. To address this requirement, three methodologies are proposed in this study-a hybrid methodology for extracting and integrating keywords pertaining to national pending issues, a methodology for packaging R&D information that corresponds to national pending issues, and a methodology for constructing an associative issue network based on relevant R&D information. Data analysis techniques such as text mining, social network analysis, and association rules mining are utilized for establishing these methodologies. As the experiment result, the keyword enhancement rate by the proposed integration methodology reveals to be about 42.8%. For the second objective, three key analyses were conducted and a number of association rules between national pending issue keywords and R&D keywords were derived. The experiment regarding to the third objective, which is issue clustering based on R&D keywords is still in progress and expected to give tangible results in the future.

• Journal of Practical Agriculture & Fisheries Research
• /
• v.22 no.1
• /
• pp.113-129
• /
• 2020

In this study we examined the topic analysis and correlation analysis by text mining to extract meaningful information or rules from the self introduction letter of freshman at Korea National College of Agriculture and Fisheries in 2020. The analysis items are described in items related to 'academic' and 'in-school activities' during high school. In the text mining results, the keywords of 'academic' items were 'study', 'thought', 'effort', 'problem', 'friend', and the key words of 'in-school activities' were 'activity', 'thought', 'friend', 'club', 'school' in order. As a result of the correlation analysis, the key words of 'thinking', 'studying', 'effort', and 'time' played a central role in the 'academic' item. And the key words of 'in-school activities' were 'thought', 'activity', 'school', 'time', and 'friend'. The results of frequency analysis and association analysis were visualized with word cloud and correlation graphs to make it easier to understand all the results. In the next study, TF-IDF(Term Frequency-Inverse Document Frequency) analysis using 'frequency of keywords' and 'reverse of document frequency' will be performed as a method of extracting key words from a large amount of documents.

• Journal of Korean Home Economics Education Association
• /
• v.32 no.3
• /
• pp.179-197
• /
• 2020

This study analyzed the trends in home economics education research using the language network analysis method, focusing on papers published in the KCI list for 20 years from 2000 to 2019. A total of 501 home economics education papers analyzed through word cloud, centrality analysis, and topic modeling using NetMiner 4.4, and the results are as follows. First, the number of papers in home economics education published in the KCI listing increased gradually to 186 in the 2000s and 315 in the 2010s. The academic journals in which home economics education papers were published have been diversified to 16 in the 2000s and 22 in the 2010s. 60% of all papers were published in the 'Journal of Korean Home Economics Education Association', and since 2018, the number of papers published in the 'Journal of Learner-Centered Curriculum and Instruction' has increased dramatically. Second, in the 2000s and 2010s, home economics education studies published in KCI were categorized into home economics education content analysis, home economics educational program development & application, curriculum analysis, perception survey & direction exploration. In the 2000s, 'Home Economics Teacher' appeared as the main keyword, and a lot of perception survey & direction exploration were conducted. Relatively, the influence of 'development' increased in the 2010s, and many studies were conducted to analyze home economics education contents and develop and apply home economics programs. This study has significance in that it analyzed the research trend of HEE by expanding the analysis target and analysis period of the existing studies.

• Journal of Korean Home Economics Education Association
• /
• v.33 no.4
• /
• pp.1-13
• /
• 2021

The purpose of this study is to identify trends and potential themes of research on consumption of children and adolescents for 20 years by analyzing keywords. The keywords of 869 studies on consumption of children and adolescents published in journals listed in Korean Citation Index were analyzed using text mining techniques. The most frequent keywords were found in the order of youth, youth consumers, consumer education, conspicuous consumption, consumption behavior, and character. As a result of analyzing the frequency of keywords by dividing into five-year periods, it was confirmed that the frequency of consumer education was significantly higher betwn 2006 and 2010. Research on ethical consumption has been active since 2011, and research has been conducted on various topics instead of without a prominent keyword during the most recent 5-year period. Looking at the keywords based on the TF-IDF, the keywords related to the environment and the Internet were the main keywords between 2001 and 2005. From 2006 to 2010, the TF-IDF values of media use, advertisement education, and Internet items were high. From 2011 to 2015, fair trade, green growth, green consumption, North Korean defector youths, social media, and from 2016 to 2020, text mining, sustainable development education, maker education, and the 2015 revised curriculum appeared as important themes. As a result of topic modeling, eight topics were derived: consumer education, mass media/peer culture, rational consumption, Hallyu/cultural industry, consumer competency, economic education, teaching and learning method, and eco-friendly/ethical consumption. As a result of network analysis, it was found that conspicuous consumption and consumer education are important topics in consumption research of children and adolescents.

• Journal of the Korean Society for information Management
• /
• v.41 no.2
• /
• pp.295-316
• /
• 2024

Analyzing research trends is essential for the sustainable development of a discipline and is important for understanding the value of prior research and laying the groundwork for subsequent research. This study aims to draw implications for the future direction of convergence research on the disclosure of information from various disciplines by comparing and analyzing the trends in disclosure of information research in Korea. For this purpose, we analyzed the publication frequency of information disclosure papers listed in the Korea Citation Index (KCI) from 2002 to 2023 and the publication trend by discipline as a time series. In addition, we compared the keyword relationships and specialized research topics of each discipline by applying network analysis and LDA topic modeling techniques to the names and keywords of papers in law, public administration, and library and information science. As a result of the analysis, the law focuses on legal regulations and policy improvement, public administration focuses on changing social needs and administrative operation methods, and LIS focuses on practical approaches to record management and disclosure of information. Based on this, future research directions include combining policy research in law with social change research in public administration and developing realistic policies and operational guidelines from the practical perspective of LIS. Such convergent research will enable the systematic and efficient implementation of disclosure of information systems, contributing to the guarantee of the public's right to know and the enhancement of state transparency.

• Information Systems Review
• /
• v.19 no.2
• /
• pp.1-19
• /
• 2017

Original scripts of e-learning lectures for the CEOs of corporation S were analyzed using topic analysis, which is a text mining method. Twenty-two topics were extracted based on the keywords chosen from five-year records that ranged from 2011 to 2015. Research analysis was then conducted on various issues. Promising topics were selected through evaluation and element analysis of the members of each topic. In management and economics, members demonstrated high satisfaction and interest toward topics in marketing strategy, human resource management, and communication. Philosophy, history of war, and history demonstrated high interest and satisfaction in the field of humanities, whereas mind health showed high interest and satisfaction in the field of in lifestyle. Studies were also conducted to identify topics on the proportion of content, but these studies failed to increase member satisfaction. In the field of IT, educational content responds sensitively to change of the times, but it may not increase the interest and satisfaction of members. The present study found that content production for CEOs should draw out deep implications for value innovation through technology application instead of simply ending the technical aspect of information delivery. Previous studies classified contents superficially based on the name of content program when analyzing the status of content operation. However, text mining can derive deep content and subject classification based on the contents of unstructured data script. This approach can examine current shortages and necessary fields if the service contents of the themes are displayed by year. This study was based on data obtained from influential e-learning companies in Korea. Obtaining practical results was difficult because data were not acquired from portal sites or social networking service. The content of e-learning trends of CEOs were analyzed. Data analysis was also conducted on the intellectual interests of CEOs in each field.

• The Journal of the Korea Contents Association
• /
• v.20 no.7
• /
• pp.316-330
• /
• 2020

The study analyzes reviews of hardware products, customer service products, and products that take the form of a convergence of hardware and cloud services in ICT using text mining. We derive keywords of each review and find the differentiation of words that are used to derive topics. A cluster analysis is performed to categorize reviews into their respective clusters. Through this study, we observed which keywords are most often used for each product type and found topics that express the characteristics of products and services using topic modeling. We derived keywords such as "professional" and "technician" which are topics that suggest the excellence of the service provider in the review of service products. Further, we identified adjectives with positive connotations such as "favorite", "fine", "fun", "nice", "smart", "unlimited", and "useful" from Amazon Eco review, an integrated product and service. Using the cluster analysis, the entire review was clustered into three groups, and three product type reviews exclusively resulted in belonging to each different cluster. The study analyzed the differences whereby consumer needs are expressed differently in reviews depending on the type of product and suggested that it is necessary to differentiate product planning and marketing promotion according to the product type in practice.