• 한국IT서비스학회지
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• 제17권2호
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• pp.165-177
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• 2018

Recently, online commerces are becoming more common due to factors such as mobile technology development and smart device dissemination, and online review has a big influence on potential buyer's purchase decision. This study presents a set of analytical methodologies for understanding the meaning of customer reviews of products in online transaction. Using techniques currently developed in deep learning are implemented Hierarchical Attention Network for analyze meaning in online reviews. By using these techniques, we could solve time consuming pre-data analysis time problem and multiple topic problems. To this end, this study analyzes customer reviews of laptops sold in domestic online shopping malls. Our result successfully demonstrates over 90% classification accuracy. Therefore, this study classified the unstructured text data in the semantic analysis and confirmed the practical application possibility of the review analysis process.

• 한국경영과학회지
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• 제32권2호
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• pp.53-69
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• 2007

Internet shopping websites have offered comfort to consumers in shopping and built trust relationships with them by providing electronic agents for recommendation, escrow services, and customer centers etc. But as there is little big difference among the shopping websites in terms of technical competence, website design, operational policy, they recognize online feedback (reviews or recommendation of consumers or experts) and online feedback mechanism as important marketing tools. Based on online feedback related studies, this study explores antecedents (consensus, vividness of reviews, interactions in review boards) of the perceived effectiveness of review boards which are text-based feedback mechanisms and its consequences such as trust, satisfaction, and intention to use. The results show that the perceived effectiveness of review boards is significantly affected by vividness of reviews and interactions in review boards, and the impact of interaction in review boards on the perceived effectiveness of review boards is stronger than that of vividness of reviews. The results also show that the perceived effectiveness of review boards has a significant influence on trust and satisfaction with the shopping websites, and intention to use is influenced by both trust and satisfaction.

• 한국정보시스템학회지:정보시스템연구
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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.

• 한국정보시스템학회지:정보시스템연구
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• 제31권2호
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• pp.159-177
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• 2022

Purpose Online reviews are critical for sales of online shopping platforms because they provide useful information to consumers. As the eCommerce market grows rapidly, the role of online reviews is becoming more important. The purpose of this study is to analyze how online reviews written by domestic consumers affect product sales by classifying the types of products. Design/methodology/approach This study analyzed how the effects of review characteristics(reviewer reputation, reviewer exposure, review length, time, rating, image, and emotional score) on the usefulness of online reviews differ depending on the product types. Subsequently, how the impact of review attributes (review usefulness, number of reviews, ratings, and emotional scores) on product sales differs according to each product type was compared. Based on the FCB Grid model, the product type was classified into high involvement-rational, high involvement-emotional, low involvement -rational, and low involvement-emotional product types. Findings According to the analysis result, the characteristics of reviews useful to consumers were different for each product type, and the review attributes affecting product sales were also different for each product type. This study confirmed that it revealed that product characteristics are major consideration in evaluating the review usefulness and the factors affecting product sales.

• 한국의류학회지
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• 제36권12호
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• pp.1270-1284
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• 2012

This article examines how individual differences on the need for cognitive closure and demographics influence consumer perception and the usage of consumer reviews in online shopping. Data were randomly collected from 2,381 U.S. online consumer review users through an online survey. The findings from multiple regression analyses revealed the different effects of the need for cognitive closure dimensions (i.e., preference for order and structure, preference for predictability, discomfort with ambiguity, closed-mindedness, and decisiveness) and demographic characteristics on consumer attitudes, perceived online review influence, benefits, persuasiveness, and review usage behavior. Finally, practical implications and prospects for future research are discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권10호
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• pp.2609-2626
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• 2023

The hotel industry is an example of experiential services. As consumers cannot fully evaluate the online review content and quality of their services before booking, they must rely on several online reviews to reduce their perceived risks. However, individuals face information overload owing to the explosion of online reviews. Therefore, consumer cognitive fluency is an individual's subjective experience of the difficulty in processing information. Information complexity influences the receiver's attitude, behavior, and purchase decisions. Individuals who cannot process complex information rely on the peripheral route, whereas those who can process more information prefer the central route. This study further discusses the influence of the complexity of review information on hotel ratings using online attraction review data retrieved from TripAdvisor.com. This study conducts a two-level empirical analysis to explore the factors that affect review value. First, in the Peripheral Route model, we introduce a negative binomial regression model to examine the impact of intuitive and straightforward information on hotel ratings. In the Central Route model, we use a Tobit regression model with expert reviews as moderator variables to analyze the impact of complex information on hotel ratings. According to the analysis, five-star and budget hotels have different effects on hotel ratings. These findings have immediate implications for hotel managers in terms of better identifying potentially valuable reviews.

• 패션비즈니스
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• 제20권6호
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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.

• 한국벤처창업학회:학술대회논문집
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• 한국벤처창업학회 2022년도 춘계학술대회
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• pp.123-126
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• 2022

Online reviews offer valuable information to businesses by reflecting consumer experiences about their products and services. Two important aspects of online reviews are first, the topics consumers choose to address and second, the sentiments expressed in their reviews. Building upon previous literature that shows online reviews are context-dependent, we examine the impact of topic distribution on review sentiment in South Korea and the U.S. during pre-and post-pandemic periods. After performing topic modeling on Airbnb app review data, we measure the contribution of each topic on review sentiment using SHAP values. Our results indicate variations in topic distribution trends between 2018 and 2021. Also, the order and magnitude of topics' impact on review sentiment change between pre-and post-pandemic periods for both countries. This study can help businesses to understand how topics and sentiments associated with their products and services changed after pandemic, and also help them identify areas of improvement.

• Asia pacific journal of information systems
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• 제32권3호
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• pp.514-536
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• 2022

Online reviews offer valuable information to businesses by reflecting consumer experiences about their products and services. Two crucial aspects of online reviews are the topics consumers choose to address, and the sentiments expressed in their reviews. Building upon previous literature that shows online reviews are context-dependent, we employ the Expectation-Confirmation Theory (ECT) to examine the impact of topic distribution on review sentiment in South Korea and the U.S. during pre- and post-pandemic periods. After applying a topic modeling to Airbnb app review data, we measure the contribution of each topic on review sentiment using SHAP values. Our results indicate variations in topic distribution trends between 2018 and 2021. In addition, the order and magnitude of topics' impact on review sentiment change between pre- and post-pandemic periods for both countries. This study can help businesses understand how topics and sentiments associated with their products and services changed after the pandemic and thus identify areas of improvement.

• International Journal of Internet, Broadcasting and Communication
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• 제16권3호
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• pp.281-289
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• 2024

Online consumer reviews have become the most important basis for online shopping and product sales. Fake reviews are generated to boost sales because online consumer reviews play a vital role in consumers' decision making. The prevalence of fake reviews violates the regulations of the online business environment and misleads consumers in decision making. Thus, the present research investigates the effects of reviews' linguistic characteristics (i.e., analytical thinking, authenticity) on review fakeness. Specifically, this research examines whether (1) the level of analytical thinking is lower for fake (vs. genuine) reviews (hypothesis 1) and (2) the level of authenticity is lower for fake (vs. genuine) reviews (hypothesis 2). This research analyzed user-generated hotel reviews (genuine reviews, fake reviews) collected from MTurk. Linguistic Inquiry and Word Count (LIWC) 2022 was adopted to code review contents, and the hypotheses were tested using logistic regression. Consistent with the hypotheses 1 and 2, the results indicate that (1) analyticial thinking is negatively associated with review fakeness; and (2) authenticity is negatively associated with review fakeness. The findings provide important implications to identify fake reviews based on linguistic characteristics.