• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.191-211
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• 2022

As the value of highly sustainable companies increases, ESG(Environmental, Social, and Governance) has emerged as the biggest topic of discussion for companies around the world. In addition, as domestically, more research is being done on ESG in line with global trends, it is necessary to examine ESG research trends. Accordingly, ESG academic papers that have been published for the past 10 years were collected for each year, and frequency analysis was conducted using text mining techniques regarding key themes and thesis titles. This paper analyzed the number of selected publications by year and the cumulated number of studies through bibliometric analysis. The findings suggested that the number of ESG papers is increasing each year and that academic interest in ESG-related issues continues to abound. Next, according to the results of frequency analysis of the keywords and titles of the research papers, the words- "ESG", "company", "society", "responsibility", "management", "investment", and "sustainability"- were extracted. This analysis identified the research fields and keywords that have been relevant to ESG in the past 10 years. As a result of comparing the major ESG issues presented in recent overseas studies and the common factors of the ESG key keywords presented in this study, it was confirmed that the environment is the focus of recent studies compared to previous studies. Third, it was found that the data used by domestic ESG studies mainly include the KEJI index, the KRX index, and the KCGS ESG evaluation index. After identifying the main research subjects of ESG papers, research found that 8 out of 152 domestic ESG studies were focused on SMEs. Through this study, it was possible to confirm the ESG research trend and increase in research, and future researchers divided the research topics and research keywords and presented basic data for selecting more diverse research topics. Based on both, the arguments of previous ESG studies conducted on SMEs and the results of this study, there is a lack of studies on guidelines for ESG practice and their application to SMEs, and more ESG research regarding SMEs will need to be conducted in the future.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.3
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• pp.39-51
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• 2020

This study will examine the social issues and consumer awareness of sharing parking through the method text mining. In this experiment, the topic by keyword was extracted and analyzed using TFIDF (Term frequency inverse document frequency) and LDA (Latent dirichlet allocation) technique. As a result of categorization by topic, citizens' complaints such as local government agreements, parking space negotiations, parking culture improvement, citizen participation, etc., played an important role in implementing shared parking services. The contribution of this study highly differentiated from previous studies that conducted exploratory studies using corporate and regional cases, and can be said to have a high academic contribution. In addition, based on the results obtained by utilizing the LDA analysis in this study, there is a practical contribution that it can be applied or utilized in establishing a sharing economy policy for revitalizing the local economy.

• The Journal of Information Systems
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• v.29 no.3
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• pp.237-251
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• 2020

Purpose The research was studied the hierarchical Hangul emotion index by organizing all the emotions which SNS users are thinking. As a preliminary study by the researcher, the English-based Plutchick (1980)'s emotional standard was reinterpreted in Korean, and a hashtag with implicit meaning on SNS was studied. To build a multidimensional emotion dictionary and classify three-dimensional emotions, an emotion seed was selected for the composition of seven emotion sets, and an emotion word dictionary was constructed by collecting SNS hashtags derived from each emotion seed. We also want to explore the priority of each Hangul emotion index. Design/methodology/approach In the process of transforming the matrix through the vector process of words constituting the sentence, weights were extracted using TF-IDF (Term Frequency Inverse Document Frequency), and the dimension reduction technique of the matrix in the emotion set was NMF (Nonnegative Matrix Factorization) algorithm. The emotional dimension was solved by using the characteristic value of the emotional word. The cosine distance algorithm was used to measure the distance between vectors by measuring the similarity of emotion words in the emotion set. Findings Customer needs analysis is a force to read changes in emotions, and Korean emotion word research is the customer's needs. In addition, the ranking of the emotion words within the emotion set will be a special criterion for reading the depth of the emotion. The sentiment index study of this research believes that by providing companies with effective information for emotional marketing, new business opportunities will be expanded and valued. In addition, if the emotion dictionary is eventually connected to the emotional DNA of the product, it will be possible to define the "emotional DNA", which is a set of emotions that the product should have.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.267-272
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• 2020

Macroeconomics are one of the indicators that are preceded and analyzed when analyzing stocks because it shows the movement of a country's economy as a whole. The overall economic situation at the national level, such as national income, inflation, unemployment, exchange rates, currency, interest rates, and balance of payments, has a great affect on the stock market, and economic indicators are actually correlated with stock prices. It is the main source of data for analysts to watch with interest and to determine buy and sell considering the impact on individual stock prices. Therefore, economic indicators that impact on the stock price are analyzed as leading indicators, and the stock price prediction is predicted through deep learning-based prediction, after that the actual stock price is compared. If you decide to buy or sell stocks by analysis of stock prediction, then stocks can be investments, not gambling. Therefore, this research was conducted to enable automated stock trading by using macro-indicators and deep learning algorithms in artificial intelligence.

• Journal of Korean Critical Care Nursing
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• v.11 no.2
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• pp.75-85
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• 2018

Purpose : The purpose of this study was to examine the possible direction of critical care nursing research in the future by analyzing the trends of recent Korean studies. Method : Using a database search, we selected 263 articles on critical care nursing that were published in Korean journals between 2008 and 2017. Then, we conducted an integrative review of the contents of the selected articles and analyzed the English abstracts using the relevant packages and functions of the R program. Results : The number of studies concerning critical care nursing has increased over the 10-year period, and the specific topic of each study has diversified according to the time at which it was conducted. In terms of quality, the majority of the research was published in high-level academic journals. The key words regularly studied over the past decade were: knowledge, delirium, education, restraint, stress, and infection. Studies related to vancomycin-resistant enterococci infection, compliance, and standards have decreased, while studies related to death, communication, and safety have increased. Conclusion : Randomized controlled trials and protocol research for evidence-based critical care need to be conducted, as does research on family involvement. The key word analysis of unstructured text used in this study is a relatively new method; it is suggested that this method be applied to various critical care nursing research and develop it methodologically.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.527-538
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• 2014

The demand prediction is a critical issue for the film industry. As the social media, such as Twitter and Facebook, gains momentum of late, considerable efforts are being dedicated to prediction and analysis of hit movies based on unstructured text data. For prediction of trends found in commercially successful films, the correlations between the amount of data and hit movies may be analyzed by estimating the data variation by period while opinion mining that assigns sentiment polarity score to data may be employed. However, it is not possible to understand why the audience chooses a certain movie or which attribute of a movie is preferred by using such a quantitative approach. This has limited the efforts to identify factors driving a movie's commercial success. In this regard, this study aims to investigate a movie's attributes that reflect the interests of the audience. This would be done by extracting topic keywords that represent the contents of Twits through frequency measurement based on the collected Twitter data while analyzing responses displayed by the audience. The objective is to propose factors driving a movie's commercial success.

• Herbal Formula Science
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• v.28 no.1
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• pp.15-27
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• 2020

Objectives : We selected three herb-combined remedies, Bigihwan (BGH), Daechilgitang (DCGT) and Mokwhyangbinranghwan (MHBRH), through Donguibogam text-mining analysis, and evaluated their anti-cancer effects on human hepatocellular carcinoma Hep3B cells. Methods : Cytotoxicity was assessed by an MTT assay. Apoptosis rate, autophagy and ROS level were detected by flow cytometry. The autophagy was also observed by Cyto-ID staining fluorescence microscopy. The expression of autophagy, mitophagy and pexophagy regulatory proteins was detected by Western blot analysis. Results : BGH showed the strongest effect among the three prescriptions in inhibiting Hep3B cell viability, which was associated with the induction of apoptosis and autophagy. Autophagy blockers improved cell viability and reduced apoptosis after BGH and DCGT treatments, indicating that autophagy by these prescriptions enhanced Hep3B cells against their cytotoxicity. However, MHBRH enhanced the reduction of cell viability and apoptosis by autophagy blockers. Induction of autophagy by BGH treatment was associated with mitophagy due to mitochondrial dysfunction than DCGT and MHBRH-treated cells. In addition, induction of apoptosis by BGH treatment was ROS-dependent and showed the possibility of pexophagy involvement. Conclusion : Although further studies need to be conducted to study the efficacy and mechanism of accurate anticancer activity, the present results will serve as important sources of understanding the mechanism of action of herbal remedies prescribed for liver disease as documented in Donguibogam.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.829-834
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• 2018

As the IT technology is progressing, the big data becomes more important and is exploited on the various industry. The R is the language and the environment analyzing the big data. The university which is the highest level of the academic organization keeps opening and maintaining the departments anticipating the needs of the progressing trends. As analyzing the names of the departments opened at the universities, it is possible to find out the requirements and the needs of the recent trends. In this paper, we analyze the names of the departments presented at the 4 year universities using the R. To do this, we collect the names of the departments and measure the frequency of the names in order to know the department of major frequently presented at the universities.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.231-239
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• 2017

Solar energy is attracting attention as an alternative to fossil fuels. However, there was a lack of discussion on the overall research direction and future direction of research in technology development. In order to develop more effective technology, we analyzed and discussed the technology trend of solar energy using patent data and thesis data. As an analysis method, topics were selected by using topic modeling and text mining, the increase of included keywords was analyzed, and the direction of development of solar technology was analyzed. Research on solar power generation technology is expected to proceed steadily, and it is analyzed that intensive research will be done especially on high efficiency and high performance technology. Future studies could be conducted by adding overseas patent data and various paper data.

• Informatization Policy
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• v.25 no.3
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• pp.52-74
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• 2018

In February 2018, the Korean government established the "Comprehensive Plans for Government Innovation" in order to realize 'the people-centered government'. The core of the comprehensive plans is participation of the people, which is very similar to open innovation where social issues are solved by ideas and capabilities of the private sector rather than those of the government. Therefore, this study was conducted by extracting open innovation topics through topic modeling based on LDA(Latent Dirichlet Allocation) as English abstract-data from 2003, when the plans for open innovation was first announced, to April 2018. Based on the extracted results, it also conducted a comparative analysis with "Comprehensive Plans for Government Innovation." The study has significant implications in that it derives the relationship between the subjects, analyzes the present policies of Korea on open innovation and suggests directions for development.