• 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.

• 경영정보학연구
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• 제23권1호
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• pp.1-22
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• 2021

본 연구에서는 퍼지논리 에이전트 기반 모델링(ABM: Agent-Based Modeling)을 이용한 시뮬레이션 기법을 이용하여 대표적 온라인 게임 장르인 MMORPG게임과 스포츠게임별로 게임 사용자들의 아이템 거래 행동특성을 분석하고자 한다. 온라인 게임 시장에서 아이템 거래는 게임회사의 수익성을 좌우하는 핵심변수이다. 그럼에도 불구하고, 기존 온라인 게임 연구에서는 게임 장르별로 게임 사용자들의 아이템 거래 행동특성을 면밀하게 분석하는 연구가 부족하였다. 이는 온라인 게임시장의 특성상 실증분석이 어렵기 때문이다. 이 같은 기존 연구의 한계를 극복하기 위한 방법으로 본 연구에서는 ABM을 이용한다. 한편, 게임 사용자들의 행동 특성은 게임 장르별로 달라지며 주어진 게임의 특성에 따라서 많은 편차를 보이기 때문에 그만큼 모호성과 불확실성이 수반된다. 이러한 상황을 고려하여 본 연구에서는 ABM과 퍼지 논리를 결합한 방법을 적용한다. 본 연구에서 고려한 온라인 게임 장르는 MMORPG와 스포츠게임이다. ABM과 퍼지 논리를 결합한 시뮬레이션 결과 MMORPG 게임장르에서는 사용자들이 고성능 아이템에 값비싼 가격을 지불할 동기가 있음이 확인되었다. 반면, 스포츠게임 장르의 경우 게임 사용자들은 아이템 성능 자체에는 민감하게 반응하지 않으며, 상대적으로 합리적인 가격대에서 게임 아이템 거래를 하고자 함을 알 수 있었다. 이 같은 본 연구의 분석결과로 미루어 볼 때 본 연구에서 제안하는 퍼지논리 기반의 ABM 시뮬레이션 기법은 온라인 게임사가 게임 아이템 관리 및 고객 이탈방지전략 수립 시 유용하게 사용될 가능성이 충분한 도구임을 알 수 있었다.

• 한국정보시스템학회지:정보시스템연구
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• 제30권4호
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• pp.303-327
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• 2021

Purpose The online comments on news content have become social information and are understood based on deliberative democracy. Although the related research has focused on the relationship between online comments and their deliberative quality, the social information provided by online comments consists of not only direct information such as comments themselves but also indirect information such as 'likes' and 'dislikes'. Therefore, the research on online comments and deliberative quality should study this direct and indirect information together, and the direction and the degree of the indirect information should be also considered with them. Design/methodology/approach This study distinguishes comments by the attached 'likes' and 'dislikes', identifies highly supported and highly unsupported comments by the intensity of 'likes' and 'dislikes', and investigates the relationship between their existence and the deliberative quality measured as the topic diversity. Then, we applied topic modeling to the 2,390 news articles and their 74,385 comments collected from five news sites. Findings The topic diversities of the supported and unsupported comments are related to the topic diversity of all comments but the degree of the relationship is higher in the case of supported comments. Furthermore, the existence of highly supported and unsupported comments is led to less diversity of all comments compared to the case where those comments are absent. Particularly, when only highly supported comments are present, topic diversity was lower than in the opposite case.

• 한국콘텐츠학회논문지
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• 제22권7호
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• pp.30-45
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• 2022

본 연구에서는 텍스트마이닝을 활용해 한국과 미국의 온라인 뉴스와 포럼에서 산업수학과 관련한 이슈를 파악하고, 그 결과를 비교 분석하였다. 이를 위해 한국의 주요 포털 사이트인 네이버의 뉴스 기사, 클리앙의 게시글과 댓글, 그리고 미국의 New York Times와 CNN의 뉴스 기사, Reddit의 게시글과 댓글에서 산업수학과 관련한 텍스트 데이터를 수집하여 구조적 토픽모델링 분석을 수행하였다. 주요 분석결과는 다음과 같다. 첫째, 한국의 뉴스는 산업수학의 필요성과 정부의 지원 측면에 대해, 미국에서는 산업수학이 활용되는 다양한 분야에 대해 다루는 것으로 나타났다. 둘째, 한국에서는 온라인 뉴스와 포럼에서 각기 다른 주제로 동일한 개수의 이슈가 나타났지만, 미국에서는 온라인 포럼보다 뉴스 기사에서 더 많은 이슈를 다루고 있는 것으로 나타났다. 이를 토대로 한국에서 산업수학이 정착하는 데 있어 연구자들에게는 학술적, 그리고 정부에는 실무적 시사점을 제시하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2200-2203
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• 2003

In an active noise control(ANC) system using the Filtered-X least mean square(LMS) algorithm, the online secondary path modeling method by exploiting a random noise generator is applied. This method is suitable for secondary path modeling. However, it is increased the residual error of the ANC system. In this paper, we presents an ANC system improved online secondary path modeling method which is modified Kuo and Zhang model that is the secondary path estimation by the additive noise. In addition, our proposed model is used that additive noise is transformed into the signal multiplied reference signal by gain control parameter and delayed.

• Journal of Information Science Theory and Practice
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• 제10권3호
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• pp.40-56
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• 2022

This paper aims to implement a topic modeling technique for extracting the topics of online discussions among library professionals in India. Topic modeling is the established text mining technique popularly used for modeling text data from Twitter, Facebook, Yelp, and other social media platforms. The present study modeled the online discussions of Library and Information Science (LIS) professionals posted on Lis Links. The text data of these posts was extracted using a program written in R using the package "rvest." The data was pre-processed to remove blank posts, posts having text in non-English fonts, punctuation, URLs, emails, etc. Topic modeling with the Latent Dirichlet Allocation algorithm was applied to the pre-processed corpus to identify each topic associated with the posts. The frequency analysis of the occurrence of words in the text corpus was calculated. The results found that the most frequent words included: library, information, university, librarian, book, professional, science, research, paper, question, answer, and management. This shows that the LIS professionals actively discussed exams, research, and library operations on the forum of Lis Links. The study categorized the online discussions on Lis Links into ten topics, i.e. "LIS Recruitment," "LIS Issues," "Other Discussion," "LIS Education," "LIS Research," "LIS Exams," "General Information related to Library," "LIS Admission," "Library and Professional Activities," and "Information Communication Technology (ICT)." It was found that the majority of the posts belonged to "LIS Exam," followed by "Other Discussions" and "General Information related to the Library."

• 전기학회논문지
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• 제59권5호
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• pp.1001-1004
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• 2010

Acoustic feedback and background noise variation can degrade the performance of an active noise control (ANC) system. In this paper, nonlinear ANC using a non-parametric VSS-NLMS (or NPVSS-NLMS) algorithm and online feedback path modeling is proposed, whereby the conventional linear ANC with online acoustic feedback-path modeling is further extended to nonlinear Volterra ANC with a linear acoustic feedback path. In particular, the step-size of the NPVSS-NLMS algorithm is controlled to reduce the effect of background noise variation in the ANC system. Simulation results demonstrate that the proposed approach yields better nonlinear ANC performance compared with the conventional nonlinear ANC method.

• Asia pacific journal of information systems
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• 제29권2호
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• pp.181-202
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• 2019

The purpose of this study is to explore the effect of different types of simultaneous presentation (i.e., reviewer information, textual and visual content, and similarity between textual-visual contents) on review usefulness and review enjoyment in online restaurant reviews (ORRs), as they are interrelated yet have rarely been examined together in previous research. By using Latent Dirichlet Allocation (LDA) topic modeling and state-of-the-art machine learning (ML) methodologies, we found that review readability in textual content and salient objects in images in visual content have a significant impact on both review usefulness and review enjoyment. Moreover, similarity between textual-visual contents was found to be a major factor in determining review usefulness but not review enjoyment. As for reviewer information, reputation, expertise, and location of residence, these were found to be significantly related to review enjoyment. This study contributes to the body of knowledge on ORRs and provides valuable implications for general users and managers in the hospitality and tourism industries.

• 대한가정학회지
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• 제47권7호
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• pp.73-82
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• 2009

The purpose of this study was to examine the effect of perceived justice associated with service recovery on perceived service quality, and the relationships among perceived service quality, customer satisfaction and behavioral intentions in online apparel shopping contexts. Justice theory provided the theoretical framework for this study. The research strategy employed an online survey methodology. Online shoppers (N=669) who had experiences in service failure and dissatisfactions completed a questionnaire. The model of the study was tested by structural equation modeling (SEM) and the results of SEM revealed positive effect of perceived justice regarding service recovery on perceived service quality, positive effect of perceived service quality on customer satisfaction, and positive effect of customer satisfaction on behavioral intention. The results of this study have implications for online retailers. Online retailers need to understand the importance of service recovery by which service failures are managed.

• 한국IT서비스학회지
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• 제13권3호
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• pp.183-200
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• 2014

Online brand communities have become a major component of marketing strategy given that these communities encourage participation and share the culture of Web 2.0 core concepts to Internet users. This study investigated the effects of social capital and knowledge quality on the success of online brand communities. A research model suggests that trust among members and the identification derived from social capital theory and knowledge quality influence individual community participation; knowledge quality also influences brand trust. In turn, community participation and brand trust develop brand loyalty. The model was empirically analyzed using structural equation modeling with data from online brand community members in Korea. The results indicate that identification and knowledge quality significantly affects brand trust and brand loyalty through community participation. This study provides a basis for developing a success model for online brand communities. Also, this study identifies a new role of knowledge quality in an online brand community context.