• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.1-10
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• 2021

This study empirically confirmed 'the political bias of the YouTube recommendation algorithm' and 'the selective exposure of user' to verify the Filter Bubble phenomenon of YouTube. For the experiment, two new YouTube accounts were opened and each account was trained simultaneously in a conservative and a liberal account for a week, and the "Recommended" videos were collected from each account every two days. Subsequently, through the text mining method, the goal of the research was to investigate whether conservative videos are more recommended in a righties account or lefties videos are more recommended in a lefties account. And then, this study examined if users who consumed political news videos via YouTube showed "selective exposure" received selected information according to their political orientation through a survey. As a result of the Text Mining, conservative videos are more recommended in the righties account, and liberal videos are more recommended in the lefties account. Additionally, most of the videos recommended in the righties/lefties account dealt with politically biased topics, and the topics covered in each account showed markedly definitive differences. And about 77% of the respondents showed selective exposure.

• Journal of Korea Game Society
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• v.14 no.4
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• pp.105-120
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• 2014

Many of recent studies have suggested various positive outcomes of serious games. However, relatively little emphasis has been placed on the roles of user-centered factors from a psychological perspective. One of the main goals of serious games is the change of the user's perception and behavior towards a positive direction. To achieve this goal, psychological factors should be applied to the user's playing process in serious games. Inspired by construal-level theory(CLT), we propose a CLT applied model (CLT in process-outcome serious games model) considering psychological factors on the player's decision making. The model will be useful not only to game developers or designers but also to game researchers as a valuable tool in persuasion and learning for serious game users.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.04a
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• pp.523-527
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• 2000

최근 기업에서의 인터넷 응용이 보편화되고 있으며, 인터넷 기반의 전자상거래(CALS/EC)는 선택의 문제가 아니라 생존의 수단으로 받아 들여 지고 있다. CALS/EC는 비즈니스 관련 정보를 전자적으로 교환함으로써 기존의 비즈니스 방식을 개선, 전환, 재정의하고, 비용절감, 품질향상, 서비스의 품질과 속도개선을 통해 고객만족과 기업이윤을 증대시키는 새로운 기업의 전술로 정의되고 있다. 이러한 인터넷 기반 CALS/EC의 활성화로 인해 여러 분야에서의 기업 상품에 대한 마케팅 전략 등이 최우선적으로 고려되고 있다. 본 논문에서는 이러한 전자상거래를 포함, 인터넷 이용자의 특성.취향을 분석하기 위한 이용자 특성.취향 분석 시스템의 구성원리와 그 구성요소 중 하나의 모듈인 특성화된 이용자 로그정보로부터 추적 알고리즘을 이용한 시뮬레이션을 수행함으로써, 보다 정확한 이용자 정보를 수집하여 유연성있는 정보를 제공할 수 있는 시스템을 구축하고 구현하였다.

• Journal of The Korea Institute of Healthcare Architecture
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• v.17 no.2
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• pp.53-59
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• 2011

본 연구는 미국 텍사스 주의 소도시에 있는 스캇 앤 화이트 클리닉의 외부공간을 대상으로 하여 외래환자와 방문객들이 직면하는 길찾기의 문제점을 분석한다. 연구의 공간적 범위는 클리닉의 외부공간으로 한정하여 진입도로에서 진입하여 주차한 후 출입구에 도달하는 경로에서 관찰되는 행태적 특성을 분석한다. 분석의 초점은 진입도로에서 이루어지는 경로선택의 결정과 그것이 클리닉에 진입하기 위한 출입구 결정에 미치는 영향관계에 둔다. 분석은 외부공간에서의 길찾기에 관한 기존 연구문헌을 참고하여 작성한 연구모형에 의해 이루어진다. 구체적으로 보면, 이용자들이 보이는 날씨, 성별, 그리고 나이에 따른 길찾기 행태의 차이를 클리닉의 남동측 출입구와 남서측 출입구에서 발생하는 이용자들의 하차 빈도를 측정하였다. 또한 하차의 위치를 행태 지도에 기록하여 연구모델에 나타나는 상관성을 분석하였다. 길찾기 행태분석 결과를 통해 파악된 외부주차장에 주차한 후 클리닉에 접근하는 이용자들의 경로선택의 문제점과 클리닉의 입구 공간에서 하차한 이용자들의 입구선택에서 나타나는 문제점을 토대로 하여 외부공간에서 발생하는 길찾기 행위의 효율성을 증진시키기 위한 디자인 추천 사항을 다음과 같이 제시한다: (1) 시각적 단서를 제공하기 위해 남서쪽 출입구의 형태와 색채 차별화; (2) 도로에서 클리닉 진입공간에 위치한 안내판의 글자 크기 확대; (3) 학습된 길찾기 행태를 보조하기 위해 동쪽에 랜드마크 시설물 설치 및 목적 지점의 최종경관 개선; (4) 과도한 클리닉의 정보에 의해 감소되는 가독성을 고려하여 안내판의 정보 간략화; (5) 색채의 대조를 고려(출입구 벽에 설치된 클리닉의 이름이 갈색에 푸른색으로 설치되어 있어 색채의 대비가 낮아 가독성 떨어짐); (6) 클리닉 중앙 출입구의 하차 공간 상부에 설치된 캐노피 기둥의 과도한 크기에 의해 발생하는 가시공간의 감소에 의해 발생하는 하차 공간 사용의 혼잡 문제를 제거하기 위해 기둥규모 축소; (7) 하차점 6까지 캐노피를 확장하여 우천시에 발생하는 공간 사용의 문제점 제거; 그리고 (8) 올바른 하차공간 사용을 위해 진입 접근도로에 차선 설치.

• Informatization Policy
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• v.27 no.1
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• pp.36-54
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• 2020

This study empirically analyzes the impact of digital divide between digital device usage motivation and operational skills on online political participation. The analysis was performed using the National Information Society Agency's 2018 digital divide survey data from September to December 2018 and applying the Heckman selection model to control the sample selection bias that may occur between internet users and non-users. The result shows the gap in motivation and device operational skills of individual citizens using digital devices has significant impact on online political participation. In socio-economic terms, it shows the age, education level and regional factors also have significant impact on online political participation, while gender and income levels do not. This study holds significance in that there are different patterns of digital divide between digital devices, identifying the motivation to use a digital device as an important factor for mobile device users, and the device operational skills, for personal computer users.

• Knowledge Management Research
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• v.24 no.4
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• pp.63-85
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• 2023

This study aims to identify the primary user group in the growing metaverse space based on the increased interest during the COVID-19 era. It also aims to explore the predictive factors for metaverse adoption. To predict online activities, the study examined user purposes, motivations, and relevant demographic factors as predictive variables through model analysis. The data from the Korean Media Panel Survey were used, and a two-stage analysis with the Heckman two-stage sample selection model was conducted to predict metaverse users. The analysis revealed that the key factors influencing metaverse adoption were offline activities, openness, OTT usage, and purchasing of paid content. Moreover, in the second stage model, openness, gender, and paid content purchases were identified as significant variables for increasing metaverse usage time. These results indicate that understanding metaverse users is essential in the context of the rising interest in online activities during the COVID-19 era and can provide valuable insights for metaverse platform-related companies and developers.

• The Korean Journal of Financial Management
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• v.22 no.2
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• pp.213-226
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• 2005

Adverse selection is a heavily scrutinized subject within the financial intermediary industry. Consensus is reached regarding its effect on the loan interest rate. Despite the similar features of financial service offered by the credit card, we still have controversy regarding credit card interest rate on how is adverse selection incurred with the change of interest rate. Thus, this paper explores how does the adverse selection, if ever, take place and affect the credit card interest rate. Information asymmetry regarding the credit card users' type represented by the default probability is assumed. The users are assumed to be rational in that they want to minimize the per unit dollar expense associated with the commercial transaction and financing between the two typical payment methods, cash and credit card. Suppliers, i.e. credit card companies, would like to maximize their profit and would be better off with more pervasive use of credit cards over the cash. Then we could show that the increasing credit card interest rate is subject to the adverse selection, sharing the same tenet with that of the bank loan interest rate proposed by Stiglitz and Weiss. Hence the current theory predicts that credit card market also suffers from adverse selection with increasing interest rate.

• Digital Contents
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• no.8 s.123
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• pp.24-24
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• 2003

"현재 이동통신 3사의 음성요금제는 모두 203종으로, 요금제를 잘못 선택해 손해를 보는 이용자의 손해 액은 연간 2,300억 원에 이를 것으로 추산됩니다. 그 가운데 자신의 라이프 스타일에 따라 적합한 요금제를 선택할 수 있도록 도와주는 서비스로 기획된 것입니다."

• Journal of the Korean Society for Library and Information Science
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• v.46 no.2
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• pp.115-132
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• 2012

The purpose of this study is to examine the current status of user-contributed reviews for the Next Generation Library Catalogs, and the potential impact of user reviews available from the external sources, including Amazon.com and GoodReads.com. During the period of February 16th through April 4th, 2012, the number of holding libraries and user-contributed reviews, tags and reading lists of ten selected books were examined from the WorldCat. Also the user-contributed reviews for the same books available from Amazon.com and GoodReads.com were examined, and a case of reviews for one book was analyzed. The result shows that only a few users participated in the WorldCat, and user-contributed reviews were rarely used, when compared with tags or reading lists. Several hundred to thousand user-contributed reviews for the same books were available from Amazon.com and GoodReads.com directly linked with bibliographic records. A case of one book from Amazon.com reveals the possibility of distorting the function of user-contribution. With the introduction of the function of user-contribution, it is expected that its growth rate should be carefully observed and its potential impact on users should be thoroughly and systematically analyzed in the near future.

• Journal of the Korean Society for Railway
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• v.12 no.5
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• pp.656-662
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• 2009

In general, the analysis of travelers' mode choice behavior is accomplished by developing the utility functions which reflect individual's preference of mode choice according to their demographic and travel characteristics. In this paper, we propose a methodology that takes the spatial effects of individuals' departure locations into account in the mode choice model. The statistical models considered here are spatial logistic regression model and conditional autoregressive model taking a spatial association parameter into account. We employed the Bayesian approach in order to obtain more reliable parameter estimates. The proposed methodology allows us to estimate mode shares by departure places even though the survey does not cover all areas.