• 제목/요약/키워드: Star Rating

검색결과 39건 처리시간 0.025초

The Status of Paid and Free Star Chart Game Applications: Focus on Google Play in Korea

  • Nam, Sang-Zo
    • International Journal of Contents
    • /
    • 제14권3호
    • /
    • pp.46-52
    • /
    • 2018
  • The objective of this study was to determine the status of star chart game applications in the Google play store in Korea. The share of game genres in paid and free star charts of game applications was searched. Also, the average reviewer's rating, average number of reviews, and average age rating based on the genre of paid and free star charts of game applications, and the average price of paid applications based on genre were analyzed. Hypothesis tests for the differences in average reviewer's rating, average number of reviews, average age rating according to the genre of game applications were performed. Also, hypothesis tests for the differences in average reviewer's rating, average number of reviews, average age rating between the paid and free game applications along with the hypothesis test for the differences in price according to the genre of paid game applications were performed. Lastly, hypothesis tests for the correlation between the start chart ranking and number of reviews in association with the correlation between the start chart ranking and reviewer's rating were performed. Statistically significant differences in average reviewer's rating, average number of reviews, average age rating according to the genre of game applications, and between the paid and free game applications were verified. However, the correlation between the start chart ranking and number of reviews in association with the correlation between the start chart ranking and reviewer's rating were not statistically significant.

방한 관광객의 온라인 리뷰에 대한 빅데이터 분석 기반의 감성분석 및 평점 예측모형 (Sentiment Analysis and Star Rating Prediction Based on Big Data Analysis of Online Reviews of Foreign Tourists Visiting Korea)

  • 홍태호
    • 지식경영연구
    • /
    • 제23권1호
    • /
    • pp.187-201
    • /
    • 2022
  • 관광객이 작성한 온라인 리뷰는 관광산업의 관리 및 운영에 중요한 정보를 제공한다. 평점은 제품이나 서비스에 대한 정량적인 평가로 간편하지만 관광객의 진실한 태도를 반영하기 어려우며 평점과 리뷰내용에 대한 불일치 문제도 발생하고 있다. 불일치 문제는 잠재고객에게 혼동을 줄 수 있으며 구매의사결정에도 영향을 미칠 수 있다. 본 연구에서는 온라인 리뷰기반의 평점 예측모형을 통해 평점과 리뷰내용의 불일치 문제를 해결하고자 한다. 한국을 방문한 외국인 관광객이 작성한 관광지와 호텔에 대한 리뷰의 감성분석을 통해 평점과 감성의 차이를 비교하고 TF-IDF vectorization과 감성분석 결과로 변수를 선정하였다. 로짓, 인공신경망, SVM(Support Vector Machine)을 적용하여 평점을 분류하고, 인공신경망, SVR(Support Vector Regression)을 통해 평점을 예측하였다. 평점 분류모형과 예측모형 모두 불일치한 리뷰를 제거하고 감성분석을 반영한 모형에서 우수한 성과를 보여주었다. 본 연구에서 제안한 온라인 리뷰 기반의 평점 예측모형은 평점과 리뷰내용에 대한 불일치 문제를 해결하여 신뢰할 수 있는 정보를 제공하였으며 평점이 없는 온라인 리뷰에도 활용할 수 있을 것이다.

Effect of Korean Michelin Guide Review Features on Customer Satisfaction Using LIWC

  • KIM, Yoon Ji;KIM, Su Sie;CHA, Seong Soo
    • 산경연구논집
    • /
    • 제14권1호
    • /
    • pp.21-28
    • /
    • 2023
  • Purpose: This study aims to analysis the difference by Michelin rating in customer satisfaction of restaurant listed in the Korea Michelin Guide. There are opinions that the Michelin Guide's rating system and evaluation criteria are somewhat ambiguous. Research design, data, and methodology: This study collected 145 actual online reviews published on TripAdvisor to examine how the effect of the content attributes of reviews on consumer satisfaction varies according to the Michelin grade. Based on this, two studies were conducted. Study 1 examined the effect of strong and weak positive reviews on consumer satisfaction according to the rating. Study 2 examined the effect of image information on consumer satisfaction. Results: The results revealed that the lower the Michelin rating, the more positive review had a significant effect on consumer satisfaction. The higher the rating, the more image information had an effect on consumer satisfaction. Expectations for Michelin three-star restaurants are higher than those of two-star restaurants, so customers are more likely to be used negatively when writing reviews. Conclusions: Accurate information on Michelin selection criteria should be delivered so as not to form high expectations and not to disappoint. For consumers to be satisfied with the name Michelin, the standards should be stricter.

Development of the implant surgical technique and assessment rating system

  • Park, Jung-Chul;Hwang, Ji-Wan;Lee, Jung-Seok;Jung, Ui-Won;Choi, Seong-Ho;Cho, Kyoo-Sung;Chai, Jung-Kiu;Kim, Chang-Sung
    • Journal of Periodontal and Implant Science
    • /
    • 제42권1호
    • /
    • pp.25-29
    • /
    • 2012
  • Purpose: There has been no attempt to establish an objective implant surgical evaluation protocol to assess residents' surgical competence and improve their surgical outcomes. The present study presents a newly developed assessment and rating system and simulation model that can assist the teaching staffs to evaluate the surgical events and surgical skills of residents objectively. Methods: Articles published in peer-reviewed English journals were selected using several scientific databases and subsequently reviewed regarding surgical competence and assessment tools. Particularly, medical journals reporting rating and evaluation protocols for various types of medical surgeries were thoroughly analyzed. Based on these studies, an implant surgical technique assessment and rating system (iSTAR) has been developed. Also, a specialized dental typodont was developed for the valid and reliable assessment of surgery. Results: The iSTAR consists of two parts including surgical information and task-specific checklists. Specialized simulation model was subsequently produced and can be used in combination with iSTAR. Conclusions: The assessment and rating system provided may serve as a reference guide for teaching staffs to evaluate the residents' implant surgical techniques.

The Effect of Rating Dispersion on Purchase of Experience Goods based on the Korean Movie Box Office Data

  • Chen, Lian;Choi, Kang Jun;Lee, Jae Young
    • Asia Marketing Journal
    • /
    • 제21권1호
    • /
    • pp.1-21
    • /
    • 2019
  • Online platforms often provide rating information to customers to relieve the uncertainty they encounter when purchasing experience goods. Prior research has focused mostly on the roles of rating volume and the valence of an average rating among the various possibilities. However, less frequently investigated is the effect of rating dispersion, which may be associated with uncertainty regarding how well a product fits a customer's personal preference, on new trials of experience goods. In this study, we examine the effect of rating dispersion on new trials of experience goods and identify the conditions which intensify or reduce the effect. Empirical analyses of movie box office sales data and online rating data reveal three interesting findings. First, movie sales decrease as movie ratings become increasingly dispersed. Second, the negative effect of rating dispersion on movie sales is more pronounced with more rating volume. Third, this negative effect weakens when additional information about a movie is available (i.e., higher average rating, greater star power, and time since its release). We discuss the academic and practical implications of our findings.

의사결정나무를 활용한 온라인 소비자 리뷰 평가에 영향을 주는 핵심 키워드 도출 연구: 별점과 좋아요를 중심으로 (Core Keywords Extraction forEvaluating Online Consumer Reviews Using a Decision Tree: Focusing on Star Ratings and Helpfulness Votes)

  • 민경수;유동희
    • 한국정보시스템학회지:정보시스템연구
    • /
    • 제32권3호
    • /
    • pp.133-150
    • /
    • 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.

Two Low-Loss Large Current Rectifiers Based on Low KVA Rating Wye-Connected Autotransformers

  • Meng, Fangang;Man, Zhongcheng;Li, Quanhui;Gao, Lei
    • Journal of Power Electronics
    • /
    • 제18권6호
    • /
    • pp.1697-1707
    • /
    • 2018
  • In this paper, two large current rectifiers are proposed based on two wye-connected autotransformers. The requirements of the ideal large current rectifier are analyzed, and it is concluded that the large current rectifier has a higher power density and a higher energy conversion efficiency when it is made up of two three-phase half-wave rectifiers and a wye-connected autotransformer. According to theoretical analysis results, the two novel wye-connected autotransformers are designed to feed two three-phase half-wave rectifiers. The two autotransformers can generate two groups of three-phase voltages with a 60o phase shifting, and their kVA ratings account for 95% and 80% of the load power, respectively. These values are less than those of a double star rectifier at 30% and 46%. From the input mains and output side, the power quality of the proposed rectifiers is the same as that of the double star rectifier. Some experiments validate the correctness of the theoretical analysis.

중국내 극장 개봉영화 흥행에 영향을 미치는 요인 (Factors Affecting Box Office Performance in China)

  • 기선;유세경
    • 한국콘텐츠학회논문지
    • /
    • 제18권5호
    • /
    • pp.357-366
    • /
    • 2018
  • 본 연구는 2015년 중국 극장에서 개봉된 200편 영화를 대상으로 영화 흥행 수익에 영향을 미치는 요인들에 대해 분석하였다. 회귀분석결과 중국 극장 개봉영화 흥행에 유의미하게 영향을 미치는 요인들은 주연배우인기지수, 온라인평점, 제작사 파워, 중국제작영화여부 였으며, 배급사 파워, 영화의 장르, IP활용여부, 제작사/배급사 결합여부는 유의하지 않은 것으로 나타났다. 이는 영화의 장르가 주요한 영향을 미쳤던 기존 연구결과와는 차이가 있으며, 인터넷으로 평가되는 주연 배우 인기지수, 온라인 평점 등이 흥행수익에 영향을 미치는 가장 중요한 요소로 나타나 중국 극장에서 상영되는 영화 흥행에 온라인 마케팅 요소가 영향을 미치는 주요한 요인으로 부각되고 있음을 알 수 있다.

제품 사용 기간을 반영한 기계학습 기반 사용자 평가 변화 예측 모델 (Machine Learning-based model for predicting changes in user evaluation reflecting the period of the product)

  • 부현경;김남규
    • 디지털산업정보학회논문지
    • /
    • 제19권1호
    • /
    • pp.91-107
    • /
    • 2023
  • With the recent expansion of the commerce ecosystem, a large number of user evaluations have been produced. Accordingly, attempts to create business insights using user evaluation data have been actively made. However, since user evaluation can change after the user experiences the product, it is difficult to say that the analysis based only on reviews immediately after purchase fully reflects the user's evaluation of the product. Moreover, studies conducted so far on user evaluation have overlooked the fact that the length of time a user has used a product can affect the user's product evaluation. Therefore, in this study, we build a model that predicts the direction of change in the user's rating after use from the user's rating and reviews immediately after purchase. In particular, the proposed model reflects the product's period of use in predicting the change direction of the star rating. However, since the posterior information on the duration of product use cannot be used as input in the inference process, we propose a structure that utilizes information about the product's period of use using an auxiliary classifier. As a result of an experiment using 599,889 user evaluation data collected from the shopping platform 'N' company, we confirmed that the proposed model performed better than the existing model in terms of accuracy.