• 제목/요약/키워드: Reviews analysis

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인터넷 쇼핑몰의 패션 상품 구매후기가 소비자의 신뢰, 만족, 몰입 및 재구매의도에 미치는 영향 (The Effect of Purchase Reviews on the Trust, Satisfaction, Commitment, and Repurchase Intention of Consumer in Internet Shopping Malls)

  • 홍병숙;이은진;조미애
    • 한국의류학회지
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    • 제33권11호
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    • pp.1817-1827
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    • 2009
  • This study analyzes how the purchase reviews of fashion merchandise influence consumer trust, satisfaction, commitment, word-of-mouth intention, and repurchase intention in internet shopping malls. The survey was conducted from October $15^{th}$ to December $5^{th}$ in 2008, and 368 responses were used in the data analysis. The statistical analysis methods were frequency analysis, factor analysis, reliability analysis, and multiple regression analysis. The results show that the purchase reviews factors of fashion merchandise in internet shopping malls were amusement, assentation, overstatement, genuineness, and usefulness. The assentation, genuineness, and usefulness of purchase reviews have an effect on consumer trust and satisfaction. The amusement, overstatement, and usefulness of purchase reviews have an effect on the emotional commitment of consumers, while the amusement, assentation, overstatement, genuineness, and usefulness of purchase reviews influence the reasonable commitment of consumers. Consumer trust and commitment effect word-of-mouth intention and repurchase intention in internet shopping malls.

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.

소비자의 특성이 온라인 상품평 활용의도에 미치는 영향 (Effect of Consumer Characteristics on Intention to Use Product Reviews to Make Online Purchasing Decisions)

  • 박윤주
    • 한국IT서비스학회지
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    • 제16권2호
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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.

Analysis of Online Reviews on Hotel Booking Intention: An Empirical Study in Indonesia

  • Hendro, WIDJANARKO;Farhvisa Muzakka, ABDILLAH;Dyah, SUGANDINI
    • The Journal of Asian Finance, Economics and Business
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    • 제10권2호
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    • pp.83-90
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    • 2023
  • This study aims to determine the direct effect of positive online reviews, negative online reviews, the usefulness of online reviews, reviewers' expertise, timeliness of online reviews, the volume of online reviews, and comprehensiveness of online reviews on accommodation booking intentions and also the indirect effect of positive online reviews on the intention of booking accommodations through trust as mediation. Research respondents are users of the accommodation booking application in Yogyakarta. Hypothesis testing was carried out using SEM (Partial Least Square). Data was collected by distributing questionnaires to 135 respondents. The results of this study indicate that the Usefulness of Online Reviews, Volume of Online Reviews, and Comprehensiveness of Online Reviews have a direct positive and significant influence on the accommodation booking Intention of booking application users in Yogyakarta. The variables of Negative Online Reviews and Timeliness of Online Reviews have negative and significant influences on the accommodation booking Intention of booking application users in Yogyakarta. Positive Online Reviews and Reviewer Expertise variables are not significant in this study. At the same time, the Trust variable has a full mediation relationship in an indirect relationship between the Positive Online Reviews variables and the accommodation booking Intention of booking application users in Yogyakarta.

Exploration of Fit Reviews and its Impact on Ratings of Rental Dresses

  • Shin, Eonyou;McKinney, Ellen
    • Fashion, Industry and Education
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    • 제15권2호
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    • pp.1-10
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    • 2017
  • The purposes of this study were to explore (1) how fit reviews differ among height groups and (2) how overall numerical ratings differ depending on height groups and ifferent types of fit reviews. Content analysis was used to analyze systematically sampled online consumer reviews (OCRs) of formalwear dresses rented online. In part 1, 201 OCRs were analyzed to develop the coding scheme, which included three aspects of fit (physical, aesthetic, and functional), valence (negative, neutral, positive), and overall numerical rating. In part 2, 600 OCRs were coded and statistically analyzed. Differences in frequency were not found among height groups for any types of mentions (negative, neutral, and positive) in terms of the three aspects of fit in the OCRs. Differences in overall mean ratings were not found among height groups. Interestingly, valence of each aspect of fit reviews affected mean numeric ratings. This study is new in examining relationships among textual information (i.e., fit reviews), numerical information (i.e., numerical rating), and reviewer's characteristic (i.e., height). The results of this study offered practical implications for etailers and marketers that they should pay attention to the three aspects of fit reviews and monitor garments with negative fit evaluations for lower ratings. They may attempt to increase ratings by providing customers recommendations to get a better fit.

온라인 쇼핑몰의 상품평 자동분류를 위한 감성분석 알고리즘 (A Sentiment Analysis Algorithm for Automatic Product Reviews Classification in On-Line Shopping Mall)

  • 장재영
    • 한국전자거래학회지
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    • 제14권4호
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    • pp.19-33
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    • 2009
  • 급속한 전자상거래의 발전으로 인하여 온라인상으로 상품을 구매하고 그에 대한 평가를 작성하는 것이 일반적인 구매 패턴이 되었다. 기존 구매자들의 상품평들은 다른 잠재적인 소비자들의 상품 구입을 이끌어내는데 큰 동기가 된다. 사용자가 작성한 상품평은 하나의 상품에 대해 실제 사용자의 좋고 나쁨에 대한 감정을 표현한 결과로, 개개인에 따라 긍정 또는 부정적인 의견으로 나눠진다. 상품평 중에서 소비자가 원하는 정보를 얻기 위해서는 이들을 일일이 수작업으로 확인해야하지만, 온라인 쇼핑몰에 상품평이 대용량으로 축적된 환경에서 이러한 작업은 비효율적일 수밖에 없다. 본 논문에서는 오피니언 마이닝 기술을 이용하여 제품 사용자의 주관적 의견을 자동으로 분류할 수 있는 감성분석 알고리즘을 제시한다. 본 논문에서 제시하는 알고리즘은 온라인 쇼핑몰에 등록된 개별 상품평을 대상으로 긍정 및 부정 의견으로 판단하여 요약된 결과를 제공하는 기능을 한다. 본 논문에서는 또한 제안된 알고리즘을 바탕으로 개발된 상품평 자동분석 시스템을 소개하고, 알고리즘의 효율성을 검증하기 위한 실험결과도 제시한다.

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코로나19 팬데믹 상황에서 감성분석을 이용한 미국, 중국, 한국 여행자의 온라인 리뷰 비교 분석 (A Comparative Analysis of Travelers' Online Reviews among China, USA, and South Korea using Sentiment Analysis in the Era of the COVID-19 Pandemic)

  • 홍준우;홍태호
    • 한국IT서비스학회지
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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.

A Comparative Evaluation of Airline Service Quality Using Online Content Analysis: A Case Study of Korean vs. International Airlines

  • Peter Ractham;Alan Abrahams;Richard Gruss;Eojina Kim;Zachary Davis;Laddawan Kaewkitipong
    • Asia pacific journal of information systems
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    • 제31권4호
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    • pp.491-526
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    • 2021
  • Airlines can employ a variety of quality monitoring procedures. In this study, we employ a content analysis of 8 years of online reviews for Korean airlines in contrast to other international airlines. Online airline reviews are infrequent, relative to the total number of passengers - the number of reviews is multiple orders of magnitude lower than passenger volumes - and online airline reviews are, therefore, not representative of passenger attitudes overall. Nevertheless, online reviews may be indicative of specific service issues, and draw attention to aspects that require further study by airline operators. Furthermore, significant words and phrases used in these airline reviews may help airline operators to rapidly automate filtering, partitioning, and analysis of incoming passenger comments via other channels, including email, social media posts, and call center transcripts. The current study provides insights into the contents of online reviews of Korean vs Other-International airlines, and opportunities for service enhancement. Further, we provide a set of marker words and phrases that may be helpful for management dashboards that require automated partitioning of passenger comments.

빅데이터 텍스트 마이닝을 활용한 소비자 리뷰에서의 의류 소재 키워드 분석 (Keywords Analysis of Clothing Materials in Consumer Reviews Using Big Data Text Mining)

  • 강가은;박지원;유신정
    • 한국의류학회지
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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.

토픽 모델링을 활용한 한의원 리뷰 분석과 마케팅 제언 (Reviews Analysis of Korean Clinics Using LDA Topic Modeling)

  • 김초명;조아람;김양균
    • 대한한의학회지
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    • 제43권1호
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    • pp.73-86
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    • 2022
  • Objectives: In the health care industry, the influence of online reviews is growing. As medical services are provided mainly by providers, those services have been managed by hospitals and clinics. However, direct promotions of medical services by providers are legally forbidden. Due to this reason, consumers, like patients and clients, search a lot of reviews on the Internet to get any information about hospitals, treatments, prices, etc. It can be determined that online reviews indicate the quality of hospitals, and that analysis should be done for sustainable hospital marketing. Method: Using a Python-based crawler, we collected reviews, written by real patients, who had experienced Korean medicine, about more than 14,000 reviews. To extract the most representative words, reviews were divided by positive and negative; after that reviews were pre-processed to get only nouns and adjectives to get TF(Term Frequency), DF(Document Frequency), and TF-IDF(Term Frequency - Inverse Document Frequency). Finally, to get some topics about reviews, aggregations of extracted words were analyzed by using LDA(Latent Dirichlet Allocation) methods. To avoid overlap, the number of topics is set by Davis visualization. Results and Conclusions: 6 and 3 topics extracted in each positive/negative review, analyzed by LDA Topic Model. The main factors, consisting of topics were 1) Response to patients and customers. 2) Customized treatment (consultation) and management. 3) Hospital/Clinic's environments.