• Title/Summary/Keyword: Online Review Analysis

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A Study of Online Reviews Affecting Non-Face-to-Face Shopping

  • LYU, Moon Sang
    • 산경연구논집
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    • 제14권1호
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    • pp.67-74
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    • 2023
  • Purpose: This study aims to investigate how the online review usefulness affect consumers' shopping behavior in non-face-to-face shopping, which is now very common format of shopping environment after COVID-19 pandemic. Factors influencing online reviews were determined as quantity of review, agreement of review and characteristic of review based on research by existing researchers. Research design, data, and methodology: Customers in their teens to 60s who had experience of checking online reviews and purchasing products were surveyed using a Google questionnaire form from January 15, 2022 to February 19, 2022. To verify the validity and reliability of the research model, confirmatory factor analysis and discriminant validity analysis were conducted. In addition, the causal relationship between factors was verified through path analysis. Results: As a result, quantity of review and agreement of review had a statistically significant effect on review usefulness. However, characteristic of review did not have a statistically significant influence on review usefulness. And review usefulness had a statistically significant effect on attitude and purchase intention. Conclusions: This study investigated the factors affecting usefulness of online reviews and empirically analyzed the effects of online reviews on consumer attitudes and purchase intentions providing practical and theoretical implications for corporate online review management.

Hierarchical Attention Network를 활용한 주제에 따른 온라인 고객 리뷰 분석 모델 (Analysis of the Online Review Based on the Theme Using the Hierarchical Attention Network)

  • 장인호;박기연;이준기
    • 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.

온라인 리뷰의 텍스트 마이닝에 기반한 한국방문 외국인 관광객의 문화적 특성 연구 (A study on cultural characteristics of foreign tourists visiting Korea based on text mining of online review)

  • 야오즈옌;김은미;홍태호
    • 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.

온라인 구매후기 작성동기가 패션제품 재구매의도 및 추천의도에 미치는 영향 (The Effect of Online Review Writing Motives of Internet Shopping on Repurchase Intention and Recommendation Intention about Fashion Merchandise)

  • 구태희;구양숙
    • 한국의류산업학회지
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    • 제12권2호
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    • pp.188-193
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    • 2010
  • The purpose of this study was to investigate the online review writing motives of online shopping on repurchase intention and recommendation intention about fashion merchandise. The questionnaire was administered to 279 people who had experience in online shopping. The data were analyzed by utilizing factor analysis, multiple regression analysis and t-test. The results of this study were as follow. First, the online review writing motives were divided into three categories such as benefit pursuit/hedonic shopping value, information transmission and evaluation. Second, the consumer who has experience of writing review prefers to repurchase other products in that online shopping mall and to recommend those products more than the consumer who doesn't have that experience. Third, the benefit pursuit/hedonic and information transmission had an effect on repurchasing intention and recommendation intention.

리뷰어의 속성이 온라인 리뷰 유용성에 미치는 영향에 관한 연구 (A Study on the Effect of Reviewer's Attributes on the Usefulness of Online Review)

  • 야오즈옌;박영기;홍태호
    • 한국정보시스템학회지:정보시스템연구
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    • 제29권2호
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    • pp.173-195
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    • 2020
  • Purpose The purpose of this study is to verify the effect of reviewer's attributes on review usefulness while exploring the variables that can moderate the relationship between reviewer's attributes and review usefulness through empirical analysis. Design/methodology/approach To understand the impact of online reviewer profiles on review usefulness and how these impacts change, this study collected more than 30,000 online reviews of restaurants through TripAdvisor.com, that is a representative OTA shares tourism information. We analyze the moderating effects of four variables such as review length, review equivocality, review uncertainty, and review readability. Findings According to the empirical analysis result, this study reveals that the reviewer's profile attribute can significantly improve the review usefulness of the reviewer, and confirmed the moderating effect of the review's attribute(Review length, Equivocality, Uncertainty, Readability).

온라인 게임 리뷰의 특성이 리뷰 유용성에 미치는 영향: 토픽모델링을 활용하여 (The Impacts of Online Game Reviews' Characteristics on Review Helpfulness: Based on Topic Modeling Analysis)

  • 배성훈;김현묵;이의준;이새롬
    • 한국정보시스템학회지:정보시스템연구
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    • 제31권4호
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    • pp.161-187
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    • 2022
  • Purpose This study analyzed the topic of game review contents and how the characteristics of game reviews affect the reviews helpfulness. In addition, this study explore the content of game reviews according to the game's sales strategy such as early access strategy and releasing without early access. Design/methodology/approach We collected a list of 3,572 action genre games released in 2020. 58,336 online reviews were collected by random sampling 50 reviews in each games, and topic modeling was performed on those reviews. We dynamized the results of topic modeling and analyzed the effect on review helpfulness with multiple regression analysis. Findings The results of analysis indicate that the longer the review is or the shorter the time it is written, the more helpful the review is. In addition the topic with positive and negative review has a significant effect on the review helpfulness. As a result of exploratory analysis, games from early access had relatively fewer reviews of story-related topics than games that were released without early access. These findings can present direct guidelines for collecting specific opinions from customers in the game industry when releasing games.

쿠팡 리뷰가 상품 매출에 미치는 영향 분석 : FCB Grid Model을 기준으로 (The Impact of Coupang Reviews on Product Sales : Based on FCB Grid Model)

  • 류성관;이지영;이상우
    • 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.

글로벌 화장품 브랜드의 소비자 만족도 분석: 텍스트마이닝 기반의 사용자 후기 분석을 중심으로 (Customer Satisfaction Analysis for Global Cosmetic Brands: Text-mining Based Online Review Analysis)

  • 박재훈;김예림;강수빈
    • 품질경영학회지
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    • 제49권4호
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    • pp.595-607
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    • 2021
  • Purpose: This study introduces a systematic framework to evaluate service satisfaction of cosmetic brands through online review analysis utilizing Text-Mining technique. Methods: The framework assumes that the service satisfaction is evaluated by positive comments from online reviews. That is, the service satisfaction of a cosmetic brand is evaluated higher as more positive opinions are commented in the online reviews. This study focuses on two approaches. First, it collects online review comments from the top 50 global cosmetic brands and evaluates customer service satisfaction for each cosmetic brands by applying Sentimental Analysis and Latent Dirichlet Allocation. Second, it analyzes the determinants that induce or influence service satisfaction and suggests the guidelines for cosmetic brands with low satisfaction to improve their service satisfaction. Results: For the satisfaction evaluation, online review data were extracted from the top 50 global cosmetic brands in the world based on 2018 sales announced by Brand Finance in the UK. As a result of the satisfaction analysis, it was found that overall there were more positive opinions than negative opinions and the averages for polarity, subjectivity, positive ratio, and negative ratio were calculated as 0.50, 0.76, 0.57, and 0.19, respectively. Polarity, subjectivity and positive ratio showed the opposite pattern to negative ratio, and although there was a slight difference in fluctuation range and ranking between them, the patterns are almost same. Conclusion: The usefulness of the proposed framework was verified through case study. Although some studies have suggested a method to analyze online reviews, they didn't deal with the satisfaction evaluation among competitors and cause analysis. This study is different from previous studies in that it evaluates service satisfaction from a relative point of view among cosmetic brands and analyze determinants.

The Effect of Review Behavior on the Reviewer's Valence in Online Retailing

  • Oh, Yun-Kyung
    • 유통과학연구
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    • 제15권10호
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    • pp.41-50
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    • 2017
  • Purpose - Online product review has become a crucial part of the online retailer's market performance for a wide range of products. This research aims to investigate how an individual reviewer's review frequency and timing affect her/his average attitude toward products. Research design, data, and methodology - To conduct reviewer-level analysis, this study uses 42,172 posted online review messages generated by 6,941 identified reviewers for 59 movies released in the South Korea from July 2015 to December 2015. This study adopts Tobit model specification to take into account the censored nature and the selection bias arising from the nature of J-shaped distribution of movie rating. Results - Our estimation results support that the negative impact of review frequency and timing on valence. Furthermore, review timing has an inverted-U relationship with the user's average valence and enhance the negative effect of review frequency. Conclusions - This study contributes to the growing literature on the understanding how eWOM is generated at the individual consumer level. On the basis of the main empirical findings, this study provides insights into building a recommendation system in online retail store based on the consumer's review history data - frequency, timing, and valence.

Detecting Fake Reviews: Exploring the Linguistic Characteristics by Computerized Text Analysis

  • Moon-Yong Kim
    • 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.