• Knowledge Management Research
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• v.17 no.2
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• pp.165-185
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• 2016

Though Korea has received attention through an exceptional economic growth and the big K-POP fever all over the world, its happiness level is not so high. Therefore, this research aims to find not only the Korean' s condition of the happiness and unhappiness, but also the way to enhance their happiness. We collected various web data(89,127 cases from 2013/01 to 2014/12) through searching our own 26 keywords based on Alderfer's ERG Theory. Also, we tried to analyze the subjects related to happiness and unhappiness by using LDA topic modeling. As the result, the condition of happiness and unhappiness were the top topics extracted from each field. We conducted the second detailed analysis based on the data of condition of the happiness and unhappiness which are the top topics of the previous analysis. From the second analysis result, we proposed several ways to enhance happiness from the perspective of government, corporate, family, education, social welfare.This paper is meaningful because it catches the condition of happiness and unhappiness based on a real web data as well as transform the data into the knowledge. Also, this paper provides the practical methods from the view from all walks of life that may enhance happiness and relieve unhappiness.

• The Journal of Information Systems
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• v.31 no.2
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• pp.239-261
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• 2022

Purpose The purpose of this study is to explore and compare changes in tourist opinion during the COVID-19 pandemic. Since the COVID-19 outbreak has caused changes in all areas of our lives, the conditions related to confinement during a lockdown have led to changes in tourists' habits and behaviors. Design/methodology/approach To analyze opinion changes about tourist attractions, this study performed topic modeling by summarizing topics into five dimensions: management, scenery, price, suggestion, and safety; then, based on the topic modeling results, sentiment analysis and emotion analysis were conducted to explore the change of tourists' opinion during the COVID-19 pandemic. Findings According to the results, this study confirmed the pandemic's positive effect on tourists' opinions about attractions after the COVID 19 outbreak. Presumably due to the absence of lines and crowed. Moreover, the dimension 'Safety' started to appear in US tourists' attractions reviews only in the period after the outbreak and during the mass vaccination. These results mean that tourists started to care more about safety due to the impact of the COVID-19 pandemic.

• Journal of Information Science Theory and Practice
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• v.11 no.3
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• pp.29-42
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• 2023

This study explored issues related to the library in the COVID-19 era in YouTube videos in Korea. This study performed social network analysis and topic modeling analysis by collecting 479 YouTube videos, 20,545 words, and 8,379 channels related to COVID-19 and the library from 2019 to 2020. The study results confirmed that YouTube, a social media platform, was used as an important medium to connect users and physical libraries and provide/promote online library services. In the study, major topics and keywords such as quarantine, vlog, and library identity during the COVID-19 pandemic, library services and functions, and introductions and user guides of libraries were derived. Additionally, it was identified that videos about COVID-19 and the library are being produced by various actors (news and media channels, libraries, government agencies, librarians, and individual users). However, the study also identified that the actor network is fragmented through the channel network, showing a low density or weak linkage, and that the centrality of the library in the actor network is weak.

• Journal of Information Science Theory and Practice
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• v.10 no.3
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• pp.40-56
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• 2022

This paper aims to implement a topic modeling technique for extracting the topics of online discussions among library professionals in India. Topic modeling is the established text mining technique popularly used for modeling text data from Twitter, Facebook, Yelp, and other social media platforms. The present study modeled the online discussions of Library and Information Science (LIS) professionals posted on Lis Links. The text data of these posts was extracted using a program written in R using the package "rvest." The data was pre-processed to remove blank posts, posts having text in non-English fonts, punctuation, URLs, emails, etc. Topic modeling with the Latent Dirichlet Allocation algorithm was applied to the pre-processed corpus to identify each topic associated with the posts. The frequency analysis of the occurrence of words in the text corpus was calculated. The results found that the most frequent words included: library, information, university, librarian, book, professional, science, research, paper, question, answer, and management. This shows that the LIS professionals actively discussed exams, research, and library operations on the forum of Lis Links. The study categorized the online discussions on Lis Links into ten topics, i.e. "LIS Recruitment," "LIS Issues," "Other Discussion," "LIS Education," "LIS Research," "LIS Exams," "General Information related to Library," "LIS Admission," "Library and Professional Activities," and "Information Communication Technology (ICT)." It was found that the majority of the posts belonged to "LIS Exam," followed by "Other Discussions" and "General Information related to the Library."

• Journal of Engineering Education Research
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• v.25 no.5
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• pp.85-93
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• 2022

Capstone Design, a project-based learning technique, is the most important curriculum that clarifying major knowledge and cultivating the ability to apply through the process of solving problems in the industrial field centered on the student project team. Accordingly, various and extensive studies are being conducted for the successful implementation of capstone design courses. Unlike previous studies, this study aimed to quantitatively analyze the opinions that recorded the experiences and feelings of students who performed capstone design, and used text mining methodologies such as frequency analysis, correlation analysis, topic modeling, and sentiment analysis. As a result of examining the overall opinions of the latter period through frequency analysis and correlation analysis, there was a difference between the languages used by the students in the opinions according to gender and project results. Through topic modeling analysis, 'topic selection' and 'the relationship between team members' showed an increase in occupancy or high occupancy, and topics such as 'presentation', 'leadership', and 'feeling what they felt' showed a tendency to decreasing occupancy. Lastly, sentiment analysis has found that female students showed more neutral emotions than male students, and the passed group showed more negative emotions than the non-passed group and less neutral emotions. Based on these findings, students' practical recognition of the curriculum was considered and implications for the improvement of capstone design were presented.

• Journal of Korean Library and Information Science Society
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• v.50 no.4
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• pp.339-358
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• 2019

The purpose of this study is to understand the topics of the research for the establishment of cooperative platform between libraries, archives, and museums that carry out the common task of providing knowledge information in a broad sense. To achieve the purpose of this study, 637 bibliographic information on three institutions were collected from the Web version of Scopus database. Among the collected bibliographic information, 5,218 words were extracted through NetMiner V.4 and analysed topic modeling. The results are as follows: First, as a result of analyzing the frequency of word appearance according to the tf-idf weight 'Preservation' was the most hottest topic. Second, the topic modeling analysis through LDA(Latent Dirichlet Allocation) algorithm resulted in 13 topic areas. Third, as a result of expressing 13 topic areas as a network, repository construction was the central topic, and the research topics such as cooperation among institutions, conservation environment for collections, system and policy discovery, life cycle of collections, exhibition of information resources, and information retrieval were closely related to the central topic. Fourth, the trend of 13 topic areas by year 1998 is limited to the specific subjects such as system and policy discovery, information retrieval, and life cycle of collections, while the subsequent studies have been carried out after that year.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.539-547
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• 2023

In recent years, university education has emphasized a learner-centered education model with a change in educational paradigm. This study aims to explore students' diverse opinions and improve the quality of education by analyzing the open-ended responses of university lecture evaluations using topic modeling. To this end, a total of 45,001 open-ended responses based on the results of lecture evaluations from 2017 to 2022 in non-metropolitan universities were divided into majors and liberal arts, and a short-form optimized Biterm Topic Modeling (BTM) analysis was conducted. As a result of the analysis, major lectures were divided into "attitude toward non-face-to-face classroom experience", "attitude toward questions and discussions", "attitude toward attendance and grading", "attitude toward practical activities and presentations", and "attitude toward communication and collaboration", while liberal arts lectures were divided into "attitude toward non-face-to-face classroom experience", "attitude toward grades and evaluations", "attitude toward attendance and syllabus", "attitude toward academic knowledge and interest", and "attitude toward communication and questions". The results of this study, which analyzed various feedback from students, provide insights that can be used to compare the characteristics of majors and liberal arts courses and improve teaching and learning experiences.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.817-837
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• 2019

The medical industry is rapidly evolving into a combination of artificial intelligence (AI) and ICT technology, such as mobile health, wireless medical, telemedicine and precision medical care. Medical artificial intelligence can be diagnosed and treated, and autonomous surgical robots can be operated. For smart medical services, data such as medical information and personal medical information are needed. AI is being developed to integrate with companies such as Google, Facebook, IBM and others in the health care field. Telemedicine services are also becoming available. However, security issues of medical information for smart medical industry are becoming important. It can have a devastating impact on life through hacking of medical devices through vulnerable areas. Research on medical information is proceeding on the necessity of privacy and privacy protection. However, there is a lack of research on the practical measures for protecting medical information and the seriousness of security threats. Therefore, in this study, we want to confirm the research trend by collecting data related to medical information in recent 5 years. In this study, smart medical related papers from 2014 to 2018 were collected using smart medical topics, and the medical information papers were rearranged based on this. Research trend analysis uses topic modeling technique for topic information. The result constructs topic network based on relation of topics and grasps main trend through topic.

• Knowledge Management Research
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• v.18 no.4
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• pp.97-118
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• 2017

Thanks to the development of social media, general users become information and knowledge providers. But customers also feel difficulty to decide their purchases due to numerous information. Although recommender systems are trying to solve these information/knowledge overload problem, it may be asked whether they can honestly reflect customers' preferences. Especially, customers in book market consider contents of a book, recency, and price when they make a purchase. Therefore, in this study, we propose a methodology which can reflect these characteristics based on topic modeling and provide proper recommendations to customers in book market. Through experiments, our methodology shows higher performance than traditional collaborative filtering systems. Therefore, we expect that our book recommender system contributes the development of recommender systems studies and positively affect the customer satisfaction and management.

• Journal of Information Technology Applications and Management
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• v.31 no.4
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• pp.63-74
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• 2024

This study analyzes Korean and Chinese consumer perceptions of Hanbang (traditional Korean herbal) cosmetics, specifically focusing on Sulwhasoo's Jaum two-piece set. Using topic modeling, 7,000 consumer reviews from Naver (Korea) and Baidu (China) were examined to uncover the key themes that influence consumer satisfaction and dissatisfaction. The results reveal significant similarities and differences between the two markets. In both countries, the product is frequently purchased as a gift, and price sensitivity is a major concern. However, Korean consumers prioritize delivery experiences and product functionality, while Chinese consumers focus more on product quality and effectiveness. These findings highlight the need for targeted strategies in each market. For success in Korea, competitive pricing and improved logistics are crucial, whereas in China, maintaining high product quality and capitalizing on the gifting culture are essential. Additionally, global expansion requires educating consumers on the benefits of Hanbang cosmetics, ensuring product consistency, and adapting to regional preferences. This research provides valuable insights for cosmetic companies aiming to enhance their market presence both locally and internationally.