• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.44-53
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• 2016

The era of Big Data has come and the importance of Big Data has been rapidly growing. The part of transportation, the Four-Step Travel Demand Model(FSTDM), a traditional Trip-Based Model(TBM) reaches its limit. In recent years, a traffic demand forecasting method using the Activity-Based Model(ABM) emerged as a new paradigm. Given that transportation means the spatial movement of people and goods in a certain period of time, transportation could be very closely associated with spatial data. So, I mined Spatial Big Data from SNS. After that, I analyzed the character of these data from SNS and test the reliability of the data through compared with the attributes of TBM. Finally, I built a database from SNS for the operation of ABM and manipulate an ABM simulator, then I consider the result. Through this research, I was successfully able to create a spatial database from SNS and I found possibilities to overcome technical limitations on using Spatial Big Data in the transportation planning process. Moreover, it was an opportunity to seek ways of further research development.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.170-178
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• 2012

This study examines perceived homophily by the degree of self disclosure among SNS users. In this research, there were three different groups in terms of the degree of self disclosure among SNS users such as strong, medium and weak self disclosure groups The major results are as follows: Firstly, the higher the degree of self disclosure, the more social network service use. In addition, the higher the degree of self disclosure, the smaller the degree of online activity including blog and mini web page. Secondly, the higher the degree of self disclosure, the higher the degree of socio-demographic homophily. It can be argued that the strong group had much more mean scores than that of medium and weak groups in terms of regions, gender, age and vocation except nationality. Also, the higher the degree of self disclosure, the higher the degree of shared homophily except of political opinion homophily.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.2
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• pp.217-232
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• 2021

This study analyzed the characteristics of generation Z leading the trend of the fashion industry through the creative activity of Virgil Abloh. A literature review and case study were conducted together with detailing the research methodology. As a result of research, generation Z is conceptualized as a "digital native" who grows in digital technology environment with excellent visual sense. They are "SNS creators" who have influence on Social Networking Services (SNS). They are also characterized as "social activists" who reject social conventions and prejudices. They are a "leading creators" who seek to differentiate with creativity. The characteristics of generation Z in the creative activities of Virgil Abloh have a feature of digital native in that they seek visual originality. In terms of communicating with generation Z through SNS and influencer marketing, it has the characteristics of SNS creators. It expresses social activists in providing consumers with diversity, and social perceptions of differentiation. In terms of providing content that encourages consumers to express their personality, it has a feature of leading creators. It is meaningful in that it contributes to the understanding of the market change and marketing strategy according to the consumer development and the activity of the fashion designer.

• Convergence Security Journal
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• v.16 no.2
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• pp.25-34
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• 2016

This study aims to prevent the serious threat from dangerous person or group by responding or blocking or separating illegal activities by use of SNA: Social Network Analysis. SNA enables to identify the complex social relation of suspect and individuals in order to enhance the effectiveness and efficiency of investigation. SNS has rapidly developed and expanded without restriction of physical distance and geo-location for making new relation among people and sharing large amount of information. As rise of SNS(facebook and twitter) related crimes, terrorist group 'ISIS' has used their website for promotion of their activity and recruitment. The use of SNS costs relatively lower than other methods to achieve their goals so it has been widely used by terrorist groups. Since it has a significant ripple effect, it is imperative to stop their activity. Therefore, this study precisely describes criminal and terrorist activities on SNS and demonstrates how effectively detect, block and respond against their activities. Further study is also suggested.

• The Journal of Korean Association of Computer Education
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• v.18 no.5
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• pp.35-44
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• 2015

The purpose of this study was to explore predicting the factors affecting knowledge sharing behavior in SNS based learning community. Besides, participative motivation, openness to diversity, and knowledge sharing intention were included as predictors for this study. In addition, this study investigated the mediating role of knowledge sharing intention between participative motivation, openness to diversity and knowledge sharing behavior. 81 people in SNS based learning community participated in this study. Data collected were analyzed by correlation analysis, regression analysis and Baron & Kenny's(1986) mediation analysis. Results from this study, knowledge sharing intention and activity-oriented motivation predicted knowledge sharing behavior. In addition, knowledge sharing intention mediated among activity-oriented motivation, openness to diversity and knowledge sharing behavior.

• Journal of Digital Contents Society
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• v.12 no.3
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• pp.361-370
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• 2011

Recent popularity of the smartphone market, with the explosive growth of mobile location-based SNS(Social Network Service), is into the mainstream. SNS aims to cooperate and share information with all users, but mobile SNS is still not easy people with disabilities. In addition to using the Web, it has difficulty to provide an appropriate interface to access such as smartphone for people with disabilities. This paper will specify and analyze the context-awareness technology and SNS function, and study a variety of information that students with disabilities such as time, location and activity states including data collection and analysis of the situation by converting the status information. It has provide that students with disabilities to lead comfortable life in school according to the various types of disabilities, and school information and safety services using mobile location-based SNS.

• Journal of Digital Convergence
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• v.18 no.5
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• pp.441-453
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• 2020

This study conducted a questionnaire survey on SNS users who are conducting K-POP record collection activities using SNS and verified factors affecting the intention to continue K-POP record collection activities. The main methods of analysis were exploratory factor analysis, confirmatory factor analysis, correlation analysis, and path analysis using SPSS 21.0 program and AMOS 21.0 program. The results are summarized as follows. First, compatibility for K-POP record collection activities through SNS has a positive effect on perceived usefulness, and observability also has a positive effect on perceived usefulness and perceived ease of use. Second, perceived ease of use for K-POP records collection using SNS has a positive effect on perceived usefulness. Third, perceived usefulness and perceived ease of use for K-POP records collection using SNS have a positive effect on continuous intention of K-POP records collection activity through SNS. As a result of this study, it suggests that the intention to continue the collection activities of K-POP records using SNS can be explained through the integration of innovation diffusion theory and technology acceptance model.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.137-145
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• 2016

The explosive growth of social networking services based on smart devices popularize these relationships and activities online in accordance with the far larger impact of this on the real life offline, the interest and importance for the online activity is increasing. In this study, factors affecting the SNS activity are defined by object, user, influence direction, influence distance and proposed a method to measure organic terms in effect between the SNS users. Influence Direction and Influence Strength (or Distance) are elaborated by using the existing influence measurement element such as structured data - the number of friends, the difference between the number of contacts - and the new influence measurement element such as unstructured data - gap between the former time and the latter time, preference and type of response behavior - that occur in social network service. In addition, the system for collecting and analysing data for measuring influence from social network service and the process model on the method for measuring influence is tested by using sample data on Facebook and explained the implementation probability.

• Journal of the Korea Society of Computer and Information
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• v.26 no.2
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• pp.221-227
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• 2021

In this paper, we tried to explore factors influencing the diffusion of online events through SNS by analyzing the online footprint of consumers. To this end, log data of online events conducted by "C" beer brands were collected and analyzed. The analysis unit of log data was set for each one hour, and the analyzing method used descriptive and regression analysis. Results are as follows. First, factors influencing the diffusion of the view of SNS-based online events were like, friend used coupon, and friend size. In particular, the size of friends had the greatest impact on the diffusion, which again suggests the importance of social hubs in online events. Second, factors influencing the diffusion of the number of inflows were also like, friend used coupon, and size of friends. Third, it was found that the number of reply did not affect the diffusion of views and inflows. This study is meaningful that it suggested an alternative plan to increase the effect of online events by using real data.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.9
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• pp.229-236
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• 2016

In the past, crime prediction methods utilized previous records to accurately predict crime occurrences. Yet these crime prediction models had difficulty in updating immense data. To enhance the crime prediction methods, some approaches used social network service (SNS) data in crime prediction studies, but the relationship between SNS data and crime records has not been studied thoroughly. Hence, in this paper, we analyze the relationship between SNS data and criminal occurrences in the perspective of crime prediction. Using Latent Dirichlet Allocation (LDA), we extract tweets that included any words regarding criminal occurrences and analyze the changes in tweet frequency according to the crime records. We then calculate the number of tweets including crime related words and investigate accordingly depending on crime occurrences. Our experimental results demonstrate that there is a difference in crime related tweet occurrences when criminal activity occurs. Moreover, our results show that SNS data analysis will be helpful in crime prediction model as there are certain patterns in tweet occurrences before and after the crime.