• Journal of Information Technology Services
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• v.20 no.5
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• pp.159-176
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• 2021

In this study, we performed a comparative analysis of the sentiment value for the tourists in USA, China, and Korea on the COVID19 pandemic era to explore and find out the features of the tourists by using online reviews. We collected a total of 243,826 online hotel reviews for metropolitan city and vacation spot in the three countries to compare the features between the business and the vacation trips. We collected the online reviews into the tow groups from Jan. 1, 2019 to Nov. 31, 2019 for before COVID19 pandemic and from Apr. 1, 2020 to Deb 28, 2021 for during COVID19. Online reviews were categorized into 6 dimensions using LDA model. Sentiment analysis were presented for 6 dimensions by utilizing a lexicon base. We proposed an approach to analyzing the importance of each attribute by applying 6-dimensional sentiment values to conjoint analysis. Our empirical analysis showed that the proposed approach could explore and find out the changed features of travelers during the COVID19 pandemic.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.20 no.4
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• pp.5-15
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• 2009

This article proposed a new online union catalog of children's material owned by children's libraries and public libraries in Korea. In order to meet users' information needs about children's material the existing access points in the online catalogs should be expanded including such information as children's age, type of publication, genre, subject, theme, book review, awarded books, and location. Since location information about a particular material is essential to users, a national online union catalog of children's material should be constructed.

• Information Systems Review
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• v.17 no.3
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• pp.95-111
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• 2015

The recommendation system automatically provides the predicted items which are expected to be purchased by analyzing the previous customer behaviors. This recommendation system has been applied to many e-commerce businesses, and it is generating positive effects on user convenience as well as the company's revenue. However, there are several limitations of the existing recommendation systems. They do not reflect specific criteria for evaluating products or the factors that affect customer buying decisions. Thus, our research proposes a collaborative recommendation model algorithm that utilizes each customer's online product reviews. This study deploys topic modeling method for customer opinion mining. Also, it adopts a kernel-based machine learning concept by selecting kernels explaining individual similarities in accordance with customers' purchase history and online reviews. Our study further applies a multiple kernel learning algorithm to integrate the kernelsinto a combined model for predicting the product ratings, and it verifies its validity with a data set (including purchased item, product rating, and online review) of BestBuy, an online consumer electronics store. This study theoretically implicates by suggesting a new method for the online recommendation system, i.e., a collaborative recommendation method using topic modeling and kernel-based learning.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.10
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• pp.215-225
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• 2022

This study investigates employees' online reviews, conducts in-depth text topic mining, effectively summarizes the dimensions of employer brand value, and seeks effective ways to build employer brands from a multi-dimensional perspective. This study employs samples of employer reviews, filter keywords according to word frequency-inverse document frequency, builds a review network containing the same keywords, explore the community and summarize the theme dimensions. Simultaneously, it makes a dynamic comparison and analysis of the employer brand value dimension of different industries and enterprises. The study shows that the community exploration theme can be summarized into 11 dimensions of employer brand value, and the dimensions of employer brand value are significantly different across industries and among different enterprises within the industry. The attention to the employer brand value dimension has a significant time change. Various industries pay increasing attention to the dimension of work intensity and career development, while employers pay steady attention to the dimension of welfare benefits. The findings of this study suggest that seeking the heterogeneity of employer brand resources from the multi-dimensional differences and changes is an effective way to improve the competitiveness of enterprises in the human capital market.

• Journal of Society of Preventive Korean Medicine
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• v.26 no.1
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• pp.43-57
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• 2022

Objective : This study aims to understand the consumer's needs for Korean medicine medical service using online review analysis of medical consumers. Methods : We analyzed the purpose and satisfaction factors of medical service use using LDA (Latent Dirichlet Allocation) topic modeling. The data used in the study was 120,727 screened reviews written by medical consumers registered on Naver. The analyzed results were compared with the "2020 Korean Medicine Utilization Survey". Results : From 2018 to 2021, the five most frequently used terms were "kindness", "treatment", "doctor", "Korean medicine", and "acupuncture". The main purpose of visiting Korean medicine medical clinic and hospital was to treat "traffic accidents" in 2018, "waist(back) pain" in 2019, "musculoskeletal pain" in 2020 & 2021. Based on the rating, reviewers were satisfied with "explanation of treatment" and "treatment attitude", and dissatisfied with "accessibility to the institution". Conclusion : We concluded that the main purpose of use of Korean medicine institution was to treat musculoskeletal disorders. Based on the results of this study, it is expected that it will be used to improve Korean medicine medical service in the future.

• Journal of Distribution Science
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• v.21 no.3
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• pp.25-36
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• 2023

Purpose: Brand community in higher education institutions comes up as an important topic to be discussed because the relationships among consumers can support the institutional brand and ultimately give meaning and vitality to the market-oriented strategy. This study aims to investigate how the literature on brand community in higher education have been distributed in research trends, theoretical frameworks, and methods. Research design, data and methodology: A total of 24 articles were organized from four reputable international databases. Content analysis were performed followed by synthesis toward potential directions and suggestions. Results: The researches in this area have increasingly focused on online interaction. Social identity theory and relationship theory were the two most prevalent theories used. Since the internet provides any social relationship with a specific relationship to form the brand community, its contextualization in higher education resulted in new concept implementation. Conclusions: The relationship within online participati on has impacted the market-oriented strategy of higher education in searching for ways toward a long-term and enduring bond among students, alumni, institutions and brands. As there is a plenteous prospect of data availability combined with big data analysis technology, the online participation will pique the interest of scholars to conduct further research on it.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.838-855
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• 2019

Online product reviews are a vital source for companies in that they contain consumers' opinions of products. The earlier methods of opinion mining, which involve drawing semantic information from text, have been mostly applied in one dimension. This is not sufficient in itself to elicit reviewers' comprehensive views on products. In this paper, we propose a novel approach in opinion mining by projecting online consumers' reviews in a multidimensional framework to improve review interpretation of products. First of all, we set up a new framework consisting of six dimensions based on a marketing management theory. To calculate the distances of review sentences and each dimension, we embed words in reviews utilizing Google's pre-trained word2vector model. We classified each sentence of the reviews into the respective dimensions of our new framework. After the classification, we measured the sentiment degrees for each sentence. The results were plotted using a radar graph in which the axes are the dimensions of the framework. We tested the strategy on Amazon product reviews of the iPhone and Galaxy smartphone series with a total of around 21,000 sentences. The results showed that the radar graphs visually reflected several issues associated with the products. The proposed method is not for specific product categories. It can be generally applied for opinion mining on reviews of any product category.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.93-104
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• 2021

Most of the existing studies on the volume and valence of the eWOM (electronic word of mouth) about movies and box-office revenues were conducted using online actual data (secondary data) at Yahoo Movies, IMDB.com, Naver Movies, etc. However, it is difficult to grasp psychological variables from online actual data. Therefore, existing studies using online actual data could not identify the causal relationship among volume, valence and psychological variables. This study fills this gap in the literature. This study aims to examine the direct and indirect effects (i.e. mediating effect) of the volume and valence of online reviews about movies on purchase intention through review credibility as a mediator. We conducted a survey on the South Korean consumers and a structural equation modeling. The outcomes show that the total effects of both volume and valence are significant. In addition, volume has an indirect effect only (i.e. full mediating effect) on purchase intention through review credibility, but valence has both direct and indirect effects (i.e. partial mediating effect) on purchase intention through review credibility. The theoretical and practical implications for these results are presented.

• Journal of Information Technology Services
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• v.16 no.2
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• pp.21-32
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• 2017

This study analyzes the variable consumer characteristics that influence the intention to use online product reviews. In online e-commerce, where purchases take place without consumers seeing the products in person, the product reviews left by other consumers who have already purchased the product are believed to be valuable information. However, when different consumers read the same product review, their responses to it may vary. This study analyzes the characteristics of consumers who utilize product reviews for their purchases. Consumer characteristics are categorized into personal information, personality, purchasing tendency, and experience related to product reviews. These factors are examined to see if they have direct or indirect effects on a consumer's intention to use product reviews when making online purchases. We surveyed a total of 240 consumers who had experience using e-commerce and knew about online product reviews. Once the data was collected, path analysis was conducted using the statistics tool AMOS. The study results reveal that consumers who are female, extroverted, and have higher price sensitivity think that product reviews left by others are useful, and that this "perceived usefulness" has a positive effect on the intention to use product reviews for making online purchasing decisions. In addition, consumers who are agreeable to others, have high brand sensitivity, and who have left numerous reviews themselves demonstrated the tendency to trust reviews left by others more. Thus, we conclude that this "perceived reliability" makes it more likely that a consumer will use product reviews when making online purchasing decisions. Future research can be done to develop this study further by analyzing whether providing online product reviews corresponding to the personal characteristics of consumers enhances the effect of product reviews on online purchasing decisions.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.1
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• pp.225-254
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• 2024

The study aims to understand undergraduates' and graduate students' perceptions and satisfaction with online learning platforms and to verify the relationship between usability factors and satisfaction with online courses. The literature review facilitated the summarization of major factors to be considered in the online learning platform development process and established the research model. The follow-up survey verified the perceptions of university constituents regarding the fulfillment of the university online learning platforms' user interface principles, platforms' usability, satisfaction with platforms, and satisfaction with online courses. Causal relationships between variables were tested and modeled by analyzing survey results. We also confirmed that the same model can be applied to different types of learners and various types of online learning methods. This study is significant in verifying that the fulfillment of the platforms' user interface design principles can affect satisfaction with online courses using the platforms based on learners' evaluation results. We expect that the research model proposed in this study can contribute to the improvement and development of online learning environments in the future.