• Land and Housing Review
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• v.13 no.2
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• pp.81-90
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• 2022

This study is based on social needs for green healing spaces assumed to enhance mental health in a city. This study proposes development directions through the analysis of modern social recognition factors for neighborhood gardens. As a research method, web information data was collected using Textom among big data tools. Text Mining was conducted to extract elements and analyze their relationship through keyword analysis, network analysis, and cluster analysis. As a result, first, the healing space and the healing environment were creating an eco-friendly healthy environment in a space close to the neighborhood within the city. Second, neighborhood gardens included projects and activities that involved government, local administration, and citizens by linking facilities as well as living culture and urban environments. These gardens have been reinforced through green welfare and service programs. In conclusion, friendly gardens in the neighborhood for the purpose of public interest, which are beneficial to mental health, are green infrastructures as a healing environment that can produce positive effects.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.488-499
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• 2022

This study analyze the relationship between S&T policy and the R&D performance plans of GRIs which lack relevant research through quantitative information analysis. KISTI which is focused on the case is an ICT-based GRI that is sensitive to changes in the internal and external environment, and the impact of government S&T policy changes on KISTI's R&D performance plans was analyzed in depth.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.9
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• pp.381-390
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• 2022

Influenced by a culture that prefers non-face-to-face activity during the COVID-19 pandemic, chatbot usage is accelerating. Chatbots have been used for various purposes, not only for customer service in businesses and social conversations for fun but also for mental health. Chatbots are a platform where users can easily talk about their depressed moods because anonymity is guaranteed. However, most relevant research has been on social media data, especially Twitter data, and few studies have analyzed the commercially used chatbots data. In this study, we identified the characteristics of depressive discourse in user-chatbot interaction data by analyzing the chats, including the word 'depress,' using the topic modeling algorithm and the text-mining technique. Moreover, we compared its characteristics with those of the depressive moods in the Twitter data. Finally, we draw several design guidelines and suggest avenues for future research based on the study findings.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.287-294
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• 2022

The purpose of this study is to find out consumers' perceptions of "metaverse," a newly spotlighted technology, through big data analysis as a non-face-to-face society continues after the outbreak of COVID-19. This study conducted a big data analysis using text mining to analyze consumers' perceptions of metaverse before and after COVID-19. The top 30 keywords were extracted through word purification, and visualization was performed through network analysis and concor analysis between each keyword based on this. As a result of the analysis, it was confirmed that the non-face-to-face society continued and metaverse emerged as a trend. Previously, metaverse was focused on textual data such as SNS as a part of life logging, but after that, it began to pay attention to virtual reality space, creating many platforms and expanding industries. The limitation of this study is that since data was collected through the search frequency of portal sites, anonymity was guaranteed, so demographic characteristics were not reflected when data was collected.

• The Journal of Korean Medicine
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• v.42 no.4
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• pp.120-132
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• 2021

Objectives: The prevalence of Parkinson's disease is on an upward trend along with an increase in the aging population but there is no available treatment that halts the progression of neurodegeneration. This study reports a numerical analysis on Donguibogam and suggests novel herbal drugs, which have never been researched before but found to be deemed effective in this study. Methods: Referring to 71 Korean medicine symptom terms that represent the symptoms of Parkinson's disease, 4170 prescriptions described in Donguibogam were classified into two groups based on whether their main effects were effective for Parkinson's disease or not. Comparing the two groups, the chi-square test was performed to select statistically significant herbs, while the t-test, Wilcoxon test, and descriptive statistics were performed to determine the appropriate dose. Results: One hundred and twenty-seven prescriptions effective for Parkinson's disease were identified. The chi-square test determined 17 herbs that are effective for symptomatic treatment. Among the medicinal herbs, the authors suggest Osterici seu Notopterygii Radix et Rhizoma, Ephedrae Herba, Aconiti Tuber, Myrrha, Sinomeni Caulis et Rhizoma, and Aconiti Kusnezoffii Tuber as herbal candidates that have never been studied for Parkinson's disease. Through the statistical tests, it was judged that the mean value of the dose of the entire prescription was the appropriate dose for each herb. Conclusions: Seventeen herbs were selected for Parkinson's disease and the appropriate daily dose were calculated. Furthermore, this study presented a new process that applies a statistical method to traditional medical literature and preselecting herbs deemed effective for specific diseases.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.15-36
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• 2021

The airline industry faces with significant competition due to the rise of technology innovation and diversified customer needs. Therefore, continuous quality management is essential to gain competitive advantages. For this reason, there have been various studies to measure and manage service quality using customer reviews. However, previous studies have focused on measuring customer satisfaction only, neglecting systematic management between customer expectations and perception based on customer reviews. In response, this study suggests a framework to identify relevant criteria for service quality management, measure the importance, and assess the customer perception based on customer reviews. Machine learning techniques, topic models, and sentiment analysis are used for this study. This study can be used as an important strategic tool for evaluating service quality by identifying important factors for airline customer satisfaction while presenting a framework for identifying each airline's current service level.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.4
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• pp.65-79
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• 2022

This study identified smart manufacturing technologies using patent and topic modeling, and compared the technology development trends in countries such as the United States, Japan, Germany, China, and South Korea. To this purpose, this study collected patents in the United States and Europe between 1991 and 2020, processed patent abstracts, and identified topics by applying latent Dirichlet allocation model to the data. As a result, technologies related to smart manufacturing are divided into seven categories. At a global level, it was found that the proportion of patents in 'data processing system' and 'thermal/fluid management' technologies is increasing. Considering the fact that South Korea has relative competitiveness in thermal/fluid management technologies related to smart manufacturing, it would be a successful strategy for South Korea to promote smart manufacturing in heavy and chemical industry. This study is significant in that it overcomes the limitations of quantitative technology level evaluation proposed a new methodology that applies text mining.

• Journal of Industrial Convergence
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• v.20 no.11
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• pp.11-17
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• 2022

The development of digital technology is changing many things in our daily lives and the marketing environment of companies. Therefore, in this research, we grasp the recent overseas research trends of digital marketing. For that purpose, I would like to utilize SCOPUS, a foreign academic database, to grasp the research trends of digital marketing. As a result of the analysis, it was found that the number of digital marketing papers has been increasing continuously since 2013. In addition, as a result of topic modeling analysis, it was found that the 2nd and 4th topics were similar among the 6 topics in total, and the main topics were digital, marketing, research and so on. The results of this research are significant in that they provided information on digital marketing research trends to researchers and business practitioners. In addition, the results of this study provide practical suggestions for corporate marketers to recognize and leverage the importance of digital marketing.

• Journal of the Korean Society of Safety
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• v.38 no.3
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• pp.69-76
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• 2023

The purpose of the rules on the Occupational Safety and Health Standards (hereafter safety and health rules) is to regulate the safety and health measures stipulated in the Occupational Safety and Health Act and the specific instructions necessary for their implementation. However, the safety and health rules are extensive and complexly connected, making navigation difficult for users. In order for users to readily access safety and health rules, this study analyzed the frequency, distribution, and significance of terms included in the overall rules. First, the term distribution index was created based on the frequency and distribution of words extracted through text mining. The term distribution index derives from whether a word appears only in a specific chapter or across all rules. This allows users to effectively explore terms to be followed in a specific working environment and terms to be complied with in the overall working environment. Next, the related words of the previously derived terms were visualized through t-SNE and the Word2Vec algorithm. This can help prioritize the things that need to be managed first, focusing on key terms without checking the overall rules. Moreover, this study can help users explore safety and health rules by allowing them to understand the distribution of words and visualize related terms.

• Journal of Information Technology Services
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• v.22 no.3
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• pp.141-165
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• 2023

With the advent of the fourth industrial revolution, technologies such as the Internet of Things, artificial intelligence and cloud computing are developing rapidly, and smart homes enabled by these technologies are rapidly gaining popularity. To gain a competitive advantage in the global market, companies must understand the differences in consumer needs in different countries and cultures and develop corresponding business strategies. Therefore, this study conducts a comparative analysis of consumer reviews of smart homes in South Korea and China. This study collected online reviews of SmartThings, ThinQ, Msmarthom, and MiHome, the four most commonly used smart home apps in Korea and China. The collected review data is divided into satisfied reviews and dissatisfied reviews according to the ratings, and topics are extracted for each review dataset using LDA topic modeling. Next, the extracted topics are classified according to five evaluation factors of Perceived Usefulness, Reachability, Interoperability,Trustness, and Product Brand proposed by previous studies. Then, by comparing the importance of each evaluation factor in the two datasets of satisfaction and dissatisfaction, we find out the factors that affect consumer satisfaction and dissatisfaction, and compare the differences between users in Korea and China. We found Trustness and Reachability are very important factors. Finally, through language network analysis, the relationship between dissatisfied factors is analyzed from a more microscopic level, and improvement plans are proposed to the companies according to the analysis results.