• The Research Journal of the Costume Culture
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• v.28 no.2
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• pp.265-284
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• 2020

This study aimed to analyze the performance of Disney-collaborated fashion lines based on online consumer reviews. To do so, the researchers employed text mining and network analysis to identify key words in the reviews of these products. Blogs, internet cafes, and web documents provided by Naver, Daum, and YoutTube were selected as subjects for the analysis. The analysis period was limited to one year after for the 2019. Data collection and analysis were conducted using Python 3.7, Textom, and NodeXL. The research terms in question were as follows: 'Disney fashion collaboration' and 'Frozen fashion collaboration'. Preliminary survey results indicated that 'Elsa's dress' was the most frequently mentioned term and that the domestic fashion brand Eland Retail was the most active in selling Disney branded clothing through its own brand. The writers of reviews for Disney-collaborated fashion products were primarily mothers with daughters. Their decision to purchase these products was based upon the following factors; price, size, stability of decoration, shipping, laundry, and retailer. The motives for purchasing the product were the positive response of the consumer's child and the satisfaction of the parents due to the child's response. The problems to be solved included insufficient quantity of supply, delay in delivery, expensive price considering the number of times children's clothes are worn, poor glitter decoration, faded color, contamination from laundry, and undesirable smells immediately after the purchase.

• 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.

• The Journal of Bigdata
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• v.9 no.1
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• pp.49-60
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• 2024

This study aims to provide insights for developing innovative products, based on reviews from females aged 30 to 70 who bought cosmetic cushions via TV home shopping. Analyzing 200,000 reviews with Selenium and NLP techniques, we found the main audience is in their 50s and 60s, prioritizing radiance, blemish and wrinkle coverage, and adherence. Notably, products with appealing designs were preferred, especially for gifting among relatives and friends. The proposed innovation is Korea's first AI-recommended cushion, utilizing NLP to match customer needs. Key ingredient recommendations include S.Acamella extract and AHA components, chosen for their perceived benefits and consumer preference. The research also highlights the importance of product aesthetics and gift potential, suggesting marketing strategies should emphasize these aspects to appeal to the target demographic. This approach aims to guide product development and marketing towards meeting consumer expectations in the cosmetic cushion industry, making products more personalized and gift-worthy.

• Journal of Distribution Science
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• v.20 no.5
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• pp.13-22
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• 2022

Purpose: This study aimed to identify factors affecting attitudes and intentions toward online purchasing of millennials and gen z in Indonesia by considering distribution capabilities factors. Research design, data and methodology: This study used a non-probability sampling technique. The questionnaire was distributed through an online platform and obtained 225 respondents. The data acquired from the respondents used SPSS 23 and AMOSS 21 to process the Structural Equation Model (SEM). Results: The results of this study stated that attitudes and intentions toward online purchases were influenced by delivery speed and trust. The results also stated that the perception of web quality positively influenced trust. On the other hand, shipping tracking, people's importance to consumers, and online reviews had no significant effects on online purchasing attitudes. Conclusions: This research has made an essential contribution to increasing and expanding our understanding of factors that affect attitudes and intentions toward online shopping in a developing market, Indonesia. From a practical perspective, this research examined the integrated consumer model of millennials and Gen Z online shopping in Indonesia that considers distribution capability, trust, and perceived website quality factors. Therefore, e-commerce business actors can design e-marketing strategies and programs to achieve the company's long-term goals.

• The Journal of the Korea Contents Association
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• v.12 no.7
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• pp.323-335
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• 2012

The purpose of this study is to clarify the impact of information contents at online purchase sites of movie merchandise. The results of this study are as follows: 1) Movie-understanding information(synopsis, actors, reviews) has a meaningful influence on information service satisfaction irrespective of consumer involvement; 2) Movie-understanding and movie-going information(time, place, price, purchasing method) are alike in having a meaningful influence on online purchasing intention. However, movie-going information has a meaningful influence in case of lower consumer involvement, while movie-understanding information has a meaningful influence in case of higher consumer involvement.; 3) Information service satisfaction gives a strong influence on online purchasing intention irrespective of the level of consumer involvement. In conclusion, there is a need to improve diversity and quality of movie-understanding information to enhance consumer satisfaction. Also, it will be necessary to improve movie-understanding and movie-going information in order to enhance online purchasing intention. These results are expected to give an insight to build a creative marketing strategy of online purchase sites of movie merchandise.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.2
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• pp.41-54
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• 2019

The cinema circuit is facing a digital, network, and mobile age, which expands non-theater accessibility to movies. Application platforms are situated as the most competitive business model that provide digital content such as games, music, books, and movies. Consumers can acquire content-related information not just offline, but online as well. Therefore, item information provided by application platforms is required. The information provided by application platforms consists of richly descriptive information such as storyline summary, consumer reviews, and related articles, while non-descriptive normative information covers data such as sales ranking, release date, genre, rental or purchase cost, domestic/foreign classification, consumer rating, number of consumer ratings, film rating, and so on. In this study, we surveyed and analyzed statistically the correlation between real-time sales ranking and other comparable non-descriptive information.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Knowledge Management Research
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• v.25 no.3
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• pp.201-230
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• 2024

This study aimed to identify the factors contributing to perceived healthiness by analyzing consumer reviews of healthy restaurants. While previous studies have primarily focused on the healthiness of food products, comprehensive research from the perspective of restaurants through online review analysis is limited. To achieve this, co-occurrence network analysis and LDA topic modeling, methods of text mining, were used to investigate consumers' health-related perceptions and preferences for healthy restaurants based on a large dataset of online reviews. The analysis revealed that consumers emphasize various health-related factors such as taste, ingredient categories, freshness, price, nutritional content, healthy options, and menu diversity when choosing healthy restaurants. These factors significantly influence the evaluation and selection of restaurants. Notably, it was found that the taste of food offered in healthy restaurants is closely linked to the perception of healthiness, highlighting the importance of a healthy taste derived from ingredients. In conclusion, this study provides practical insights into how healthy restaurants can reflect and meet consumers' health perceptions and suggests strategic directions for the food and dining industry to respond to health trends.

• Journal of Fashion Business
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• v.20 no.6
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• pp.135-147
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• 2016

Online supporters are the group of people selected by companies for the online promotion of their products or services and focus on generating messages that are conducive to stimulating hands-on experiences with companies' products and services to create advertising effects. This study examined how reviews offered by blogs operated by fashion brands' online supporters influence consumer's brand attitudes and purchase intentions. Specifically, this study examined how brand awareness and directions of review messages influences consumers' brand attitudes and purchase intentions. This study employed a 2 (brand awareness: high awareness vs. low awareness) ${\times}$ 3 (review direction: one-sided positive, two-sided positive & negative, one-sided negative) between-subject factorial design. In total, 180 respondents participated, thus garnering 30 responses for each of the six conditions. The results of two-way ANOVA revealed the significant main effect supporters' review message direction on consumers' brand attitudes and purchase intentions. Two-sided messages were rated high for brand attitude and purchase intention compared to one-sided positive or negative or positive directions. The interactions between brand reputation and message direction were significant for brand attitude, but not for purchase intention.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.79-81
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• 2014

People increasingly rely on sources of information from E-commerce reviews. Product reviews is an important determinant of potential customers' buying choices. They are also utilized by product manufacturers to find problems of their products and to collect competitive intelligence information about their competitors. Unfortunately, it is well-known that many online product reviews are not made by genuine costumers of products. Reviewers could write some undeserving positive reviews to promote or fake negative reviews to defame some certain product, and we call them fake product reviews. Fake product review detection makes an attempt to detect fake reviews and removes them to restore the truthful ones for readers. To the best of our knowledge, there is still less published study on this problem. In this paper, we make a survey and an attempt to give a brief overview on fake product review detection. The related work of fake product review detection is presented including web spam and spam email. Then some methods to detect fake reviews are introduced and summarized. The trend of fake product review detection is concluded finally.