• The Journal of Information Systems
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• 제29권4호
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• pp.171-191
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• 2020

Purpose The study aims to compare the online review writing behavior of users in China and the United States through text mining on online reviews' text content. In particular, existing studies have verified that there are differences in online reviews between different cultures. Therefore, the purpose of this study is to compare the differences between reviews written by Chinese and American tourists by analyzing text contents of online reviews based on cultural theory. Design/methodology/approach This study collected and analyzed online review data for hotels, targeting Chinese and US tourists who visited Korea. Then, we analyzed review data through text mining like sentiment analysis and topic modeling analysis method based on previous research analysis. Findings The results showed that Chinese tourists gave higher ratings and relatively less negative ratings than American tourists. And American tourists have more negative sentiments and emotions in writing online reviews than Chinese tourists. Also, through the analysis results using topic modeling, it was confirmed that Chinese tourists mentioned more topics about the hotel location, room, and price, while American tourists mentioned more topics about hotel service. American tourists also mention more topics about hotels than Chinese tourists, indicating that American tourists tend to provide more information through online reviews.

• Journal of Korean Society of Industrial and Systems Engineering
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• 제44권4호
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• pp.85-97
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• 2021

Online consumer activities have increased considerably since the COVID-19 outbreak. For the products and services which have an impact on everyday life, online reviews and recommendations can play a significant role in consumer decision-making processes. Thus, to better serve their customers, online firms are required to build online-centric marketing strategies. Especially, it is essential to define core value of customers based on the online customer reviews and to propose these values to their customers. This study discovers specific perceived values of customers in regard to a certain product and service, using online customer reviews and proposes a customer value proposition methodology which enables online firms to develop more effective marketing strategies. In order to discover customers value, the methodology employs a text-mining technology, which combines a sentiment analysis and topic modeling. By the methodology, customer emotions and value factors can be more clearly defined. It is expected that online firms can better identify value elements of their respective customers, provide appropriate value propositions, and thus gain sustainable competitive advantage.

• Journal of Society of Preventive Korean Medicine
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• 제26권1호
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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 Information Technology Services
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• 제20권5호
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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.

• Proceedings of the Korea Information Processing Society Conference
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• 한국정보처리학회 2020년도 춘계학술발표대회
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• pp.389-392
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• 2020

The growth in social media, blogs and restaurant listing directories have led to increasing customer reviews about restaurants, their quality of food items and services available on the internet. These user reviews offer a massive amount of valuable information that can be used for various decision-making purposes. Currently, most food recommendation sites provide recommendation scores about restaurants rather than food items of the restaurant and the provided recommendation scores may be biased since they are calculated only from user reviews listed only in their sites. Usually, people wants a reliable recommendation about foods, not restaurant. In this paper, we present a reliable Korean food items rating method; we first extract food items by applying NER technique to restaurant reviews collected from many Korean restaurant recommendation web sites, blogs and web data. Then, we apply lexicon-based sentiment analysis on collected user reviews and predict people's opinions as sentiment polarity scores (+1 for positive; -1 for negative; 0 for neutral). Finally, by taking average of all calculated polarity scores about a food item, we obtain a rating to individual menu items of the restaurant. The proposed food item rating is more reliable since it does not depend on reviews of only one site.

• Human Ecology Research
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• 제61권3호
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• pp.475-492
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• 2023

This study investigated player responses to microtransactions in freemium Massively multiplayer online roleplaying games (MMORPG), specifically focusing on the game LostArk using English language review data. To this end, structural topic modeling was employed and the following six microtransaction-relevant topics were identified: microtransactions, developer issues, real money trade (RMT), random number generator (RNG) upgrade system, game content, and collectibles & adventure. The first four topics were classified as being "not recommended". However, the proportions of microtransaction-related topics were relatively lower than the other topics. Additionally, this study did not extract keywords related to unfairness and unethical issues in previous microtransaction research. The last two topics, game content, and collectibles & adventure were "recommended" topics, indicating positive functions of microtransactions such as enhancing the game experience by purchasing virtual items. Moreover, it was found that players who do not engage in microtransactions can still be satisfied through continuous game content updates. Additionally, an examination of the interaction effect between time and recommendation status revealed that while the frequency with which the six microtransaction-related topics were mentioned increased over time in the reviews, the ratio of recommendations to non-recommendations varied differently. This study contributes to game-related research by revealing players' authentic opinions on microtransactions in freemium MMORPGs, thereby providing practical implications for game companies.

• The Journal of Information Systems
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• 제32권3호
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• pp.133-150
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• 2023

Purpose This study aims to develop classification models using a decision tree algorithm to identify core keywords and rules influencing online consumer review evaluations for the robot vacuum cleaner on Amazon.com. The difference from previous studies is that we analyze core keywords that affect the evaluation results by dividing the subjects that evaluate online consumer reviews into self-evaluation (star ratings) and peer evaluation (helpfulness votes). We investigate whether the core keywords influencing star ratings and helpfulness votes vary across different products and whether there is a similarity in the core keywords related to star ratings or helpfulness votes across all products. Design/methodology/approach We used random under-sampling to balance the dataset. We progressively removed independent variables based on decreasing importance through backwards elimination to evaluate the classification model's performance. As a result, we identified classification models that best predict star ratings and helpfulness votes for each product's online consumer reviews. Findings We have identified that the core keywords influencing self-evaluation and peer evaluation vary across different products, and even for the same model or features, the core keywords are not consistent. Therefore, companies' producers and marketing managers need to analyze the core keywords of each product to highlight the advantages and prepare customized strategies that compensate for the shortcomings.

• Asia-Pacific Journal of Business
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• 제15권1호
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• pp.273-287
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• 2024

Purpose - This study conducts the co-occurrence analysis, one of the social network analysis using global OTA's online reviews and grades in order to understand the experience structure of foreign tourists visiting cutural tourism resources in Jeju, Korea. Design/methodology/approach - For this purpose, this study selects 6 cultural tourism resources in Jeju as the study sites, and collects qualitative review data (noun, adjectives, and verb) and quantitative grade data. Findings - The co-occurrence network analysis between words and grade of market and street shows that the grade of 5 appears the most simultaneous with pork, buy, lot, try, fresh, black, food, price, seafood, local, market, good, street, etc. and the grade of 1 connects with small, dish, better, taste, etc. And the co-occurrence network analysis between words and grade of tradition and folklore shows that the grade of 5 appears the most simultaneous with village, place, museum, visit, time, life, culture, women, diver, use, lot, etc. and the grade of 1 connects with minute, spend, room, recommend, honey, etc. Research implications or originality - The above research results are relevant in order to find out the core experience of foreign tourists using online review and grade generated by foreign tourists and use as the important information to develop the strategies related to the planning and management of cultural tourism resources.

• Journal of the Korean Society of Clothing and Textiles
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• 제48권4호
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• pp.729-743
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• 2024

This research explores consumer preferences for materials in different clothing product categories, using web-crawling and text mining techniques. Specifically, the study focuses on the material-related terms found in consumer reviews across three distinct product categories: functional clothing, formal shirts, and knit sweaters. Top-selling products within each category were identified on the Naver Shopping website based on the volume of reviews, and the four most-reviewed products were selected. Six hundred reviews per product were analyzed using the Textom big-data analysis software to determine the frequency of material-related mentions and word associations. The analysis utilized two comparative metrics: product category and usage duration. Our findings reveal notable variations in the material preferences mentioned by consumers across different product categories. The study suggests a need to re-evaluate existing standardized review criteria to better reflect consumer interests specific to each product category. Additionally, an increase in material-related terms in reviews over one month indicates the potential importance of extending the duration of product reviews to enhance the accuracy of information that reflects longer-term consumer experiences with material quality.

• Information Systems Review
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• 제24권3호
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• pp.43-68
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• 2022

With the growing demand for online food delivery (OFD) services via Online to Offline (O2O) platforms, it is required for academic researchers to identify the success factors of OFD businesses. In line with this, this research examines the impact of the core service attributes of a restaurant (hygiene, interactivity, trust,and popularity) on business success in the OFD platform context from the perspective of information asymmetry. Furthermore, the moderating effects of hygiene factor between the core service attributes and the success of restaurants are evaluated. We utilize 1,146 restaurants registered on the largest OFD platform in Korea. The results of this study demonstrate that hygiene (certification), trust (franchise), popularity (favorite) factors have positive impacts on the success of OFD businesses. Moreover, we find that franchise restaurants with high response rates to customer reviews and inquiries achieve higher sales when they have hygiene certifications than those without the certification do. The key findings bear significant contributions to prior literature by empirically substantiating the pivotal role of service quality signals in fostering restaurant success on the OFD platforms. In addition, this study provides business implications for restaurants in O2O platform.