• Journal of Digital Convergence
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• v.14 no.1
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• pp.131-139
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• 2016

Given social problems of service addiction such as mobile messenger services(MMSs), many studies on service management and information systems have examined the negative outcomes of service addiction. MMS addiction significantly influences user's health and academic performance. In this regard, this study investigated the effects of MMS addiction on user's health and academic performance problems. We posit personal traits and service features as key antecedents of MMS addiction. The research framework was tested by using survey data collected from 162 university students who have frequently used Kakaotalk. The analysis results found that MMS addiction significantly influences users' health and academic performance problems. The findings of this study indicate that self-esteem and self-control play an important role in generating MMS addiction. While attention significantly affects MMS addiction, social relationship formation and perceived enjoyment are not significantly associated with MMS addiction. The analysis results help MMS providers and government establish policies or guidelines to induce healthy MMS use.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.113-127
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• 2015

An interface in smart device environment is changing to TUI(touch user interface) environment where a system is being controlled by physical touch, differently from a system controlled through conventional mouse and keyboard. What is more important than anything else in this TUI environment is to implement interface in consideration of learn ability and cognitive constructivism according to user's experience. Therefore, now is the time when it is necessary to carry out various studies on smart content design process going a step farther together with discussing the details of user's experience factor. Hence, this study was intended to look into what effect a user's experiential traits had on the production of contents for the purpose of measures for improving TUI user satisfaction in order to effectively realize contents in smart environment. Results were yielded by using a statistical empirical analysis such as cross-tabulation analysis according to important variable and user, paired t-test, multiple response analysis, and preference frequency analysis of user preference on the basis of a survey. As a result, a system was presented for implementing DFSS(Design For Six Sigma) process. TUI experience factor can be divided into direct habitual experience, direct learning experience, indirect habitual experience, and indirect learning experience. And in the results of study, it was possible to find that the important variables of this study had a positive effect on the improvement of use satisfaction with contents on the whole according to the user convenience of smart contents. This study is expected to have a positive effect on efficient smart device-based contents production by providing objective information according to empirical analysis to smart media-based developer and designer and presenting a model for improving the changed TUI usability.

• Journal of KIISE
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• v.44 no.7
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• pp.680-685
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• 2017

The emergence of online media and their data has enabled data-driven methods to solve challenging and complex tasks such as rumor classification problems. Recently, deep learning based models have been shown as one of the fastest and the most accurate algorithms to solve such problems. These new models, however, either rely on complete data or several days-worth of data, limiting their applicability in real time. In this study, we go beyond this limit and test the possibility of super early rumor detection via recurrent neural networks (RNNs). Our model takes in social media streams as time series input, along with basic meta-information about the rumongers including the follower count and the psycholinguistic traits of rumor content itself. Based on analyzing millions of social media posts on 498 real rumors and 494 non-rumor events, our RNN-based model detected rumors with only 30 initial posts (i.e., within a few hours of rumor circulation) with remarkable F1 score of 0.74. This finding widens the scope of new possibilities for building a fast and efficient rumor detection system.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.341-343
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• 2011

이번 연구에서는 음성신호로부터 성격을 자동으로 인식하는 성격 인식 사용자 인터페이스에 대한 기술을 소개한다. 사용자의 음성대화 과정에서 말투로부터 성격 인식, 특히 외향과 내향을 구분해 내기 위해 사용되는 행동패턴에 있어서 대화중에 발생하는 생각을 위한 시간의 할애를 기초한다. 이를 바탕으로 질문이 주어진 후 이에 대한 답변을 시작하는데 걸리는 시간, 그리고 대화의 중간에 생각할 시간을 갖기 위해 활용하는 언어 주저형의 빈도수를 고려하여 사용자 성격분류의 실험을 실시하였다. 그 결과 평균적으로 약 65%의 성공률을 보였다.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.795-801
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• 2013

As the life which existed only offline has changed into a life part of which is led online, it is an important problem to identify whether an online user is legitimate one or not. Biometric authentication technology was developed to identify the user more correctly either online or in offline daily life. Biometric authentication is a technology where a person is identified by his or her unique characteristics, and is highlighted as a next-generation authentication technology replacing password. There are various kinds of traits unique to each individual, and biometric authentication technologies drawing on such traits use various devices and algorithms. Firstly, this paper classified such various biometric authentication technologies, and analyzed the effects of them when they are applied on smartphone, smartwatch and M2M of the different devices platforms. Secondly, it suggested the effectiveness-based AIB(Authentication for Integrated Biometrics) authentication technique, a comprehensive authentication technique, which can be used in different devices platforms. We have successfully included the establishment scheme of the effectiveness authentication using biometrics.

• Science of Emotion and Sensibility
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• v.17 no.1
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• pp.53-62
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• 2014

Despite the huge potential of the practical application of emotion recognition technologies, the enhancement of the technologies still remains a challenge mainly due to the difficulty of recognizing emotion. Although not perfect, human emotions can be recognized through human images and sounds. Emotion recognition technologies have been researched by extensive studies that include image-based recognition studies, sound-based studies, and both image and sound-based studies. Studies on emotion recognition through facial expression detection are especially effective as emotions are primarily expressed in human face. However, differences in user environment and their familiarity with the technologies may cause significant disparities and errors. In order to enhance the accuracy of real-time emotion recognition, it is crucial to note a mechanism of understanding and analyzing users' personality traits that contribute to the improvement of emotion recognition. This study focuses on analyzing users' personality traits and its application in the emotion recognition system to reduce errors in emotion recognition through facial expression detection and improve the accuracy of the results. In particular, the study offers a practical solution to users with subtle facial expressions or low degree of emotion expression by providing an enhanced emotion recognition function.

• Korean Journal of Social Welfare Studies
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• v.47 no.3
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• pp.5-33
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• 2016

This study investigates the current features of social service provision system focusing on the core institutional traits of the system and community environment. Specifically, the study analyzes the differences in the contents and characteristics of social service provision, according to the community types, such as metropolitan area, medium size cities, and rural area. Also, the study explores the relationships among the three major subsystems in the social service provision system based on the types of financial provisions. Furthermore, the interaction effects between the community factors and financial traits on the relationships among sub- components in the service provision system are investigated. In this study other organizations, service users and public sector are regarded as three major sub-components in the provision system. The study utilizes the raw data from '2015 Social Service Demand and Provision Survey', which interviewed 4,100 social service organizations. Results from analyses show that the gap among metropolitan area, medium cites, and rural area is not so much bigger in the diverse provision features(e.g. the competition level, the major focus on the users, and policy demands on public sector) of provider-provision-organizations than in those of both of user-provision-organization and of market-way-organizations. User-provision organizations show the distinct differences in terms of the focus points on the users, while marketed organizations do in terms of the policy demands to the public sector. In rural area, user-provision organizations act like provider-provision-organizations whereas they do market-way-organizations in the urban area. Research findings show that the social service provision types utilizing market mechanism(such as user-provision, and market-way) are not so well fit into the characteristics of rural area.

• Information Systems Review
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• v.20 no.1
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• pp.99-114
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• 2018

Technical measures for computer security are essential, but they are not a sufficient condition for security. Therefore, a personal approach to user's security behavior should be developed. Personality, which is a human aspect, is a behavioral characteristic that characterizes each individual and facilitates prediction of how an individual will behave in certain situations. Protection motivation theory has been used extensively in the security research on human behavior. The present study discusses how protection motivation was formed from personality traits. Thus, organizations can refer the result of this study for their HRD and HRM concerns.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.9-16
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• 2023

In the IoT environment, various objects mutually interactive, and various services can be composed based on this environment. In the previous study, we have developed a resource collaboration system to provide services by substituting limited resources in the user's personal device using resource collaboration. However, in the preceding system, when the number of resources and situations increases, the inference time increases exponentially. To solve this problem, this study proposes a method of classifying users and resources by applying the BIG5 user type classification model. In this paper, we propose a method to reduce the inference time by filtering the user's preferred resources through BIG5 type-based preprocessing and using the filtered resources as an input to the recommendation system. We implement the proposed method as a prototype system and show the validation of our approach through performance and user satisfaction evaluation.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.534-539
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• 2008

Nowadays, UI(User Interface)'s main target area is getting larger from user's convenience oriented interface, to user's satisfaction oriented interface. In this study, we attempted 'Storytelling User Interface' for fulfillment of user's satisfaction. We analyzed UI in games, distinguished and clarified its effectiveness that conveys main contents and special features to its audience. The most important element in storytelling UI is 'Inherent Drama'. This was proved through the game analysis with Blizzard's 'Diablo', Sierra's 'Home world', Eden Games' 'Test Drive Unlimited', EA's 'Black And White', and Sony Entertainment's 'Eye Of Judgment'. And we divided storytelling elements into 3 pieces, Mood Design - that shows story's background, or traits, Natural Control - for user's feeling as a hero in the content, and Flow Directing - using animation, visual design and sound, etc. Via these elements, we can make the best use of background, icon, animation, every structures and flow in games. Finally, we embodied three pieces for putting in practice for effective improving interface.