• 한국감성과학회:학술대회논문집
• /
• 한국감성과학회 2011년도 춘계학술대회
• /
• pp.49-50
• /
• 2011

• 보건행정학회지
• /
• 제16권2호
• /
• pp.49-76
• /
• 2006

The aim of this study was to explore the effects of a computerized review program which was introduced in August 1, 2003, using claims data for acute respiratory infection related diseases. National Health Insurance (NHI) claims data on respiratory infection related diseases before and after the introduction, with six month intervals respectively, were used for the analysis. Clinic was the unit of observation, and clinics with only one physician whose specialty was internal medicine, pediatrics, otorhinolaryngology and family medicine and clinics with a general practitioner were selected. The final sample had 7,637 clinics in total. Indices used to measure practice pattern was prescription rates of antibiotics, prescription rates of injection drug per visit, treatment costs per claim, and total costs per claim. Changes in the number of claims for major disease categories and upcoding index for disease categories were used to measure claiming behavior. Data were analysed using descriptive analysis, t-test for indices changes before and after the introduction, analysis of variance (ANOVA) for practice pattern change for major disease categories, and multiple regression analysis to identify whether new system influenced on provider' practice patterns or not. Prescription of antibiotics, prescription rates of injection drug, treatment costs per claim, and total costs per claim decreased significantly. Results from multiple regression analysis showed that a computerized review system had effects on all the indices measuring behavior. Introduction of the new system had the spillover effects on the provider's behavior in the related disease categories in addition to the effects in the target diseases, but the magnitude of the effects were bigger among the target diseases. Rates of claims for computerized review over total claims for respiratory diseases significantly decreased after the introduction of a computerized review system and rates of claims for non target diseases increased, which was also statistically significant. Distribution of the number of claims by disease categories after the introduction of a computerized review system changed so as to increase the costs per claims. Analysis of upcoding index showed index for 'other acute lower respiratory infection (J20-22)', which was included in the review target, decreased and 'otitis media (H65, H66)', which was not included in the review target, increase. Factors affecting provider's practice patterns should be taken into consideration when policies on claims review method and behavior changes. It is critical to include strategies to decrease the variations among providers.

• 한국정보시스템학회지:정보시스템연구
• /
• 제29권4호
• /
• pp.171-191
• /
• 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.

• 한국IT서비스학회지
• /
• 제15권2호
• /
• pp.169-184
• /
• 2016

Smartphone use is rapidly spreading due to the advantage of being able to connect to the Internet anytime, anywhere--and mobile app development is developing accordingly. The characteristic of the mobile app market is the ability to launch one's app into foreign markets with ease as long as the platform is the same. However, a large amount of prior research asserts that consumers behave differently depending on their culture and, from this perspective, various studies comparing the differences between consumer behaviors in different countries exist. Accordingly, this research, which uses online product reviews (OPRs) in order to analyze the cultural differences in consumer behavior comparatively by nationality, proposes to compare the U.S. and South Korea by selecting ten apps which were released in both countries in order to perform a sentimental analysis on the basis of star ratings and, based on those ratings, to interpret the sentiments in reviews. This research was carried out to determine whether, on the basis of ratings analysis, analysis of review contents for sentiment differences, analysis of LDA topic modeling, and co-occurrence analysis, actual differences in online reviews in South Korea and the U.S. exist due to cultural differences. The results confirm that the sentiments of reviews for both countries appear to be more negative than those of star ratings. Furthermore, while no great differences in high-raking review topics between the U.S. and South Korea were revealed through topic modeling and co-occurrence analyses, numerous differences in sentiment appeared-confirming that Koreans evaluated the mobile apps' specialized functions, while Americans evaluated the mobile apps in their entirety. This research reveals that differences in sentiments regarding mobile app reviews due to cultural differences between Koreans and Americans can be seen through sentiment analysis and topic modeling, and, through co-occurrence analysis, that they were able to examine trends in review-writing for each country.

• Journal of Information Processing Systems
• /
• 제18권5호
• /
• pp.650-664
• /
• 2022

Mobile applications can be easily downloaded and installed via markets. However, malware and malicious applications containing unwanted advertisements exist in these application markets. Therefore, smartphone users install applications with reference to the application review to avoid such malicious applications. An application review typically comprises contents for evaluation; however, a false review with a specific purpose can be included. Such false reviews are known as fake reviews, and they can be generated using artificial intelligence (AI)-based text-generating models. Recently, AI-based text-generating models have been developed rapidly and demonstrate high-quality generated texts. Herein, we analyze the features of fake reviews generated from Generative Pre-Training-2 (GPT-2), an AI-based text-generating model and create a model to detect those fake reviews. First, we collect a real human-written application review from Kaggle. Subsequently, we identify features of the fake review using natural language processing and statistical analysis. Next, we generate fake review detection models using five types of machine-learning models trained using identified features. In terms of the performances of the fake review detection models, we achieved average F1-scores of 0.738, 0.723, and 0.730 for the fake review, real review, and overall classifications, respectively.

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

• Clinical and Experimental Pediatrics
• /
• 제64권12호
• /
• pp.642-651
• /
• 2021

Background: Infantile colic (IC) is excessive crying in otherwise healthy children. Despite vast research efforts, its etiology remains unknown. Purpose: Most treatments for IC carry various side effects. The collection of evidence may inform researchers of new strategies for the management and treatment of IC as well as new clues for understanding its pathogenesis. This review and meta-analysis aimed to evaluate the efficacy and possible mechanisms of probiotics for mananaging IC. Methods: Ten papers met the study inclusion and exclusion criteria, and the meta-analysis was conducted using Review Manager (RevMan) software and a random-effects model. Results: This meta-analysis revealed that probiotics are effective for treating infantile colic, while the review showed that this efficacy may be due to their anti-inflammatory effects. Conclusion: Probiotics may be an important treatment option for managing infantile colic due to their anti-inflammatory properties.

• 기록학연구
• /
• 제61호
• /
• pp.157-190
• /
• 2019

기록물평가심의서는 기록물 평가업무의 과정과 결과를 담고 있다. 이 연구는 기록물관리 전문요원이 배치된 22개 교육(지원)청의 2018년 기록물평가심의서를 분석한 것이다. 분석결과의 신뢰성 확보를 위해 분석데이터 작성기준을 적용하여 데이터 작성의 일관성을 유지하고 평가절차별, 보존기간별 통계를 교차검증 하였다. 기록물평가심의서 분석을 통해 기록물평가실태를 파악하고 처리과 기록물관리, 기록물관리 전문요원의 평가업무, 기록물평가심의회 운영의 측면에서 실무에 적용 가능한 개선방안을 제안하였다.

• 정보과학회 컴퓨팅의 실제 논문지
• /
• 제22권5호
• /
• pp.209-217
• /
• 2016

스마트폰 보급의 확산으로 상품 구매 시 웹 사이트 및 SNS를 이용하여 상품 리뷰를 참고하는 소비자들이 증가하고 있다. 그러나 이러한 방식은 소비자가 직접 리뷰 데이터를 찾아 읽어야하기 때문에 시간이 오래 걸릴 뿐만 아니라 가공되지 않은 데이터가 줄 수 있는 정보는 한정적이다. 따라서 상품의 리뷰를 수집하여 기본 정보뿐만 아니라 리뷰 문장의 감정 분석을 통한 가공된 정보를 제공하는 시스템이 필요하다. 하지만 현재 이러한 상품 리뷰 분석 정보를 제공하는 시스템의 대다수는 상품의 분류와 상품의 속성을 반영하는 것이 부족하다. 본 논문에서는 상품의 분류와 속성을 반영하는 리뷰 감정 분석을 통한 전자 상거래 상품 분석 및 평가를 제공하는 시스템을 설계 및 구현하였다. 이를 도서 상품에 적용하여 구축한 시스템을 통해 소비자가 방대한 양의 상품의 리뷰 데이터를 분석할 필요 없이 상품의 속성 및 분류에 따라 가공된 분석 결과를 시각적으로 빠르게 제공받을 수 있음을 보였다.

• 경영정보학연구
• /
• 제23권1호
• /
• pp.45-68
• /
• 2021

온라인 리뷰가 소비자 의사결정에 미치는 영향이 증가함에 따라 리뷰조작에 대한 염려도 증가하고 있다. 리뷰조작은 판매량을 증가시키기 위해, 진실 되지 않은 리뷰를 게시하는 것으로 소비자의 역 선택을 초래하며, 사회 전체에 큰 비용으로 작용한다. 선행연구는 대부분 데이터 마이닝 방법을 통해 리뷰조작을 예측하는 데 초점을 맞추었으며, 소비자 관점의 연구는 상대적으로 제한적이다. 그러나 소비자가 지각한 리뷰의 조작 가능성은 리뷰의 유용성에 영향을 미칠 수 있으므로 허위 여부와 상관없이 온라인 구전 관리에 중요한 시사점을 제공할 수 있다. 따라서 본 연구에는 소비자가 조작되었다고 평가한 리뷰와 일반적인 리뷰 간에 어떠한 차이가 있는지 분석하고, 조작된 것으로 평가된 리뷰와 리뷰 유용성 간의 관계를 분석하였다. 실증분석을 위해 LibraryThing 웹사이트의 온라인 도서 리뷰 34,711개를 다수준 로지스틱 회귀분석과 포아송 회귀분석을 활용하여 분석하였다. 분석결과 소비자가 조작되었다고 지각하는 리뷰와 그렇지 않은 리뷰 간에는 제품 수준, 리뷰어 수준, 리뷰 수준 요인들에 차이가 있는 것으로 나타났다. 또한, 조작된 리뷰는 리뷰 유용성에 부정적인 영향을 미치는 것으로 나타났다.