• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.3
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• pp.205-214
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• 2016

Dramatic transformation in education has taken place and Internet Technologies have played a key role. Especially SNS has been considered as an effective educational tool because of its exceptional features such as discussion on course topics, feedback from peers and group collaboration. The purpose of this paper is to investigate factors affecting the attitude, intention to continuous use of SNS and performance in college education comparing between experienced learner and non-experienced learner. Self-efficacy on media usage, educational expectancy, subjective norm, habit, and enjoyment were identified as affecting factors based on prior researches. The results shows that all factors are significantly related to the learner's attitude on the use of SNS in college education. Experienced learner's attitude on educational use of SNS in college was found to be significantly related to the intention to continuous use and performance. This study can provide a guideline of effective strategy for SNS utilization in college education.

• The Journal of Bigdata
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• v.2 no.2
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• pp.57-66
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• 2017

Companies has been investing enormous resources in promotion as the market keeps changing rapidly. Therefore, there are growing needs to measure the impact of a promotion on revenue growth. To investigate the effect of promotion in franchise food service industry, this study empirically analyzed text data from Twitter, one of the dominant social network services. Our findings show that a gap between promotions, promotion duration, and season have a significant influence on a volume of twitter buzz, which represents a promotion effect in our study. Next, we tried to analyze the reason why those factors were related to the promotion effect. Finally, we suggested promotion strategies related to each influential factor depending on types of business in food service industry.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.326-330
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• 2012

In 2011, There were about 25,000 people died because of heart disease. The aim of this paper is to design a heart attack situation monitoring and spreading system for patients. Wearable computer with a sensor is used to monitor heart rate. Heart rate is transffered to smartphone with bluetooth. After analyzing heart rate, smartphone spread out the emergency situation by various service including emergency call, SNS and SMS.

• Journal of Digital Convergence
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• v.14 no.6
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• pp.395-403
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• 2016

This study investigates SNS usage behaviors of SNS users with a change of SNS use environment and an increase of users. This study compares the difference of use motivation, preferred type, and main use SNS according to socio-demographic variable of SNS users using cross tabulation analysis and also conducts a comparative analysis of main use SNS of each SNS user using correspondence analysis. The results show main use motivation of SNS is relationship seek, most preferred type is closed type, and main use SNS is Kakaostory. Next, we find that there are differences on use motivation, preferred type, and main use SNS, depending on the socio-demographic characteristics of SNS users. The result of correspondence analysis shows how users are using SNS services and what structure their competitive relations of SNS services are made. In the conclusion, the study presents summary of the findings, implications, and tasks for further studies.

• Journal of Korea Game Society
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• v.11 no.6
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• pp.13-22
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• 2011

In the digital media environment, the convergence is in the progress creating the new service and contents by users and developing the new needs of users by the service and contents as well. Social games are actualizing the new meaning of convergence. shows not only a new situation blurring the boundary of work and leisure, labor and playing and private and public sector, but how meaningful it is to make connection of social interactions and social assets a solid network. As the most popular social game text, reveals how the personal connections and personal networks constructs the social capital by making the ritual communication more interesting and flexible to the social gamers.

• The Journal of Korean Academic Society of Nursing Education
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• v.29 no.1
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• pp.41-50
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• 2023

Purpose: The aim of this descriptive study was to identify the factors influencing depression risk among South Korean nursing students. Methods: The data were collected from nursing students attending two universities through web-based questionnaires that surveyed them about depression, academic stress, social network service (SNS) addiction tendency, and upward social comparison from August 22 to September 4, 2021. The collected data from 196 nursing students were analyzed by t-test, one-way ANOVA, Pearson's correlation coefficients, and multiple linear regression. Results: The mean score of depression (using CES-D Korean version) among nursing students was 13.91, which denotes probable depression. Concerning the variance with regard to depression among nursing students, 20.2% was explained by clinical practice period, academic stress, and upward social comparison. Conclusion: Programs to relieve academic stress and depression should be developed in a simple way and systematically provided at the organizational level so that nursing students secure sufficient support during the initial and continuing period of clinical practicums. Concomitantly, an attempt to reduce the upward social comparison should be highly considered.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.1-12
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• 2019

This study explored the factors affecting the acceptance of public recording in SNS post. Using SPSS 21.0 program and AMOS 21.0 program, major results were derived through exploratory factor analysis, confirmatory factor analysis, correlation analysis, and path analysis. The results are as follows: First, the risk of personal information leakage on SNS posting has a significant negative impact on the attitude toward SNS posting. Second, the security of the SNS posting has a significant effect on the attitude toward the SNS posting. Third, the concern about privacy of SNS posting has a significant negative impact on the attitude toward SNS posting. Fourth, the attitude toward SNS posting has a significant effect on the intention to accept the SNS posting. The above results suggest that the SNS post recording should be able to collect opinions of SNS users from a long-term viewpoint.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.413-415
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• 2019

In this paper, we develop IoT-HiAS(IoT-Human Interactive Advertising Service) for sharing economy. The HiAS device shooting the front of the device via a webcam and recognizes the person in real time through the SSD model using MobileNet. If the number of persons above the set threshold is recognized by counting the recognized person, the advertisement is reproduced on the idle resource through the beam projector. At the same time as the advertisement is reproduced, the captured image of the advertisement start time in the front of the device and the number of recognized persons are sends the IoT server of an oneM2M-compliant HiAS server using the IoT client. When the advertisement is finish, the webcam is shooting the front of the device and the image is sends the IoT server. We implemented the IoT-based human interactive advertising service by transmitting the received data to the advertiser and the advertising producers through the SNS(Social Network Service) agent of the HiAS server.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.309-314
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• 2017

In general, there are many difficulties in collecting, storing, and analyzing SNS (social network service) data, since those data have big data characteristics, which occurs very fast with the mixture form of structured and unstructured data. In this paper, we propose a new data visualization framework that works on Apache Storm, and it can be useful for real-time and dynamic analysis of SNS data. Apache Storm is a representative big data software platform that processes and analyzes real-time streaming data in the distributed environment. Using Storm, in this paper we collect and aggregate the real-time Twitter data and dynamically visualize the aggregated results through the tag cloud. In addition to Storm-based collection and aggregation functionalities, we also design and implement a Web interface that a user gives his/her interesting keywords and confirms the visualization result of tag cloud related to the given keywords. We finally empirically show that this study makes users be able to intuitively figure out the change of the interested subject on SNS data and the visualized results be applied to many other services such as thematic trend analysis, product recommendation, and customer needs identification.

• Journal of the Korea society of information convergence
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• v.7 no.2
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• pp.49-57
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• 2014

Recently, opinion mining is introduced to extract useful information from SNS data and to evaluate the true intention of users. Opinion mining are required several efficient techniques to collect and analyze a large amount of SNS data and extract meaningful data from them. Therefore in this paper, we propose a parallel HDFS(Hadoop Distributed File System) and emotion functions based on Mapreduce to extract some emotional information of users from various unstructured big data on social networks. The experiment results have verified that the proposed system and functions perform faster than O(n) for data gathering time and loading time, and maintain stable load balancing for memory and CPU resources.