• Journal of Korean Institute of Industrial Engineers
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• v.42 no.2
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• pp.138-150
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• 2016

This study aims to analyze the structure and characteristics of the domestic online game industry using network analysis. In particular, two-mode network analysis is employed to measure the network structure, centrality, and cluster for two types of online game platforms, online games and mobile games, from 1996 to 2014. We also conduct a dynamic analysis to capture the structural changes in the ecosystem by internal and external environmental changes before and after turning point for each online game platform. It is revealed that the online game econsystem has the higher number of clusters and higher concentration ratio than those of mobile game ecosystem. In dynamic analysis, both platforms exhibit similar trends over time with the increasing number of clusters, enlargement of largest cluster's size, and decreasing concentration ratio. This study is expected to provide fruitful implications for strategic decision making of online game companies and policy making for the online game industry.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.3
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• pp.1-27
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• 2009

Since online knowledge networks usually consist of a larger, loosely knit, and geographically distributed group of "strangers" who may not know each other very well, members may not willingly share their knowledge with others. In order to address this challenge, this study looks Into the factors that are expected to affect knowledge sharing in an online knowledge network. For empirical validation, we choose "the global network of Korean scientists and engineers (KOSEN)" as one of the best practices of online knowledge networks. By using the archival, network, and survey data, we validate two models of knowledge sharing in sequence (i.e., knowledge contribution and knowledge utilization models) and then discuss the results. The findings of this study show that individuals not only contribute but also utilize knowledge in an online knowledge network when they are structurally embedded and perceive a strong reciprocity. In the network. In addition, taking pleasure in helping is found to positively affect knowledge contribution, whereas perceiving usefulness is found to Influence knowledge utilization. Contributions of this study and future research opportunities are also discussed.

• Journal of KIISE
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• v.44 no.11
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• pp.1231-1235
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• 2017

Given the network structure in online social network, it is important to determine a way to distinguish spam accounts from the network features. In online social network, the service provider attempts to detect social spamming to maintain their service quality. However the spammer group changes their strategies to avoid being detected. Even though the spammer attempts to act as legitimate users, certain distinguishable structural features are not easily changed. In this paper, we investigate a way to generate meaningful network structure features, and suggest spammer detection method using recursive structural features. From a result of real-world dataset experiment, we found that the proposed algorithm could improve the classification performance by about 8%.

• Journal of Information Technology Applications and Management
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• v.20 no.2
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• pp.177-191
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• 2013

Social network has been expected to increase the value of social capital through online user interactions which remove geographical boundary. However, online users in social networks face challenges of assessing whether the anonymous user and his/her providing information are reliable or not because of limited experiences with a small number of users. Therefore. it is vital to provide a successful trust model which builds and maintains a web of trust. This study aims to propose a prediction method for the interpersonal trust which measures the level of trust about information provider in Facebook. To develop the prediction method. we first investigated behavioral research for trust in social science and extracted 5 antecedents of trust : lenience, ability, steadiness, intimacy, and similarity. Then we measured the antecedents from the history of interactive behavior and built prediction models using the two decision trees and a computational model. We also applied the proposed method to predict interpersonal trust between Facebook users and evaluated the prediction accuracy. The predicted trust metric has dynamic feature which can be adjusted over time according to the interaction between two users.

• Asia pacific journal of information systems
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• v.31 no.3
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• pp.392-414
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• 2021

Social networking services (SNS) is an indispensable method in order to obtain information of the Internet participants. The study identified three variables of social media communication, sharing culture, and online trust in terms of social capital theory (SCT) and reviewed intention& behavior variables in terms of theory of planned behavior (TPB). The data were collected from 330 samples of SNS user, and were involved, and the research model uses AMOS to make confirmatory factor analysis. The findings confirmed our hypothesis that social media communication, sharing culture, and online trust affect individuals' behaviors to sharing information. This study emphasizes that not only social media communication but also sharing culture to SNS can stimulate information sharing. while previous research has predominately focused on personal cognition or social network, the study examines the integrated influence of communication, culture and trust on information sharing in SNS. In sum, by explicating the unique role of social capital, this paper aims at contributing to the continued development and success of SNS in general.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.116-130
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• 2019

This study investigates passenger-authored online reviews of airline services using social network analysis to compare the differences in customer perceptions between full service carriers (FSCs) and low cost carriers (LCCs). While deriving words with high frequency and weight matrix based on the text analysis for FSCs and LCCs respectively, we analyze the semantic network (betweenness centrality, eigenvector centrality, degree centrality) to compare the degree of connection between words in online reviews of each airline types using the social network analysis. Then we compare the words with high frequency and the connection degree to gauge their influences in the network. Moreover, we group eight clusters for FSCs and LCCs using the convergence of iterated correlations (CONCOR) analysis. Using the resultant clusters, we match the clusters to dimensions of two types of service quality models ($Gr{\ddot{o}}nroos$, Brady & Cronin (B&C)) to compare the airline service quality and determine which model fits better. From the semantic network analysis, FSCs are mainly related to inflight service words and LCCs are primarily related to the ground service words. The CONCOR analysis reveals that FSCs are mainly related to the dimension of outcome quality in $Gr{\ddot{o}}nroos$ model, but evenly distributed to the dimensions in B&C model. On the other hand, LCCs are primarily related to the dimensions of process quality in both $Gr{\ddot{o}}nroos$ and B&C models. From the CONCOR analysis, we also observe that B&C model fits better than $Gr{\ddot{o}}nroos$ model for the airline service because the former model can capture passenger perceptions more specifically than the latter model can.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1025-1035
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• 2013

There has been an explosive increase in the population of OSN(online social network) for 10 years. OSN provides users with many opportunities to have communication among friends, families and goes so far as to make relationships among unknown people having similar belief or interest. However, OSN also produced adverse effects such as privacy breaches, leaking uncontrolled information or disseminating false information. Access control models such as MAC, DAC, RBAC are applied to the OSN to control those problems but those models in OSN are not fit in dynamic OSN environment because user's acts in OSN are unpredictable and static access control imposes burden on users to change access control rules one by one. This paper proposes the dynamic trust-based access control to solve the problems of traditional static access control in OSN.

• Journal of Digital Convergence
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• v.18 no.1
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• pp.45-52
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• 2020

Online rumor creates psychological stress and image loss for victims. Prior studies related to online rumor did not consider the online environmental factor, despite the fact that online rumor occurs in the online space. Therefore, this study tried to investigate the influence of online characteristics on online rumor. This study considered perceived anonymity, lack of social presence, and perceived dissemination as online characteristics. We established and demonstrated a research model in which online characteristics affect online rumor behavior through attitude toward online rumor. This study obtained the sample of 201 social network users based on the survey and verified the research model using PLS tool. The results provided that perceived anonymity and perceived dissemination influenced online rumor behavior through attitude toward online rumor. On the other hand, lack of social presence was not significant. The findings of this study provide the fact that an individual's online rumor behavior can be caused by online characteristics. This study suggests that we pay attention to the role of perceived anonymity and perceived dissemination for online rumor behavior.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.109-117
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• 2021

Although previous studies on social commerce have provided much insight, more studies in the perspective of social network are needed because social commerce happens within online communities or virtual groups, where buyers connect and interact with each other by sharing information. So, the purpose of this study is to investigate how transactive memory as network characteristic can affect social commerce behavior through social support and relationship quality. We verified the relational effect among social support, relationship quality, and social commerce intention in the Korean market context. Moreover, we found transactive memory capability also played an essential role in the field of social commerce. Specifically, we found consumer's transactive memory capability plays a significant moderating role in the relation between social support and relationship quality.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.7-14
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• 2022

COVID-19 has caused a global disturbance, increased anxiety, and panic, eliciting diverse reactions. While its cure has not been discovered, new infection cases and fatalities are being recorded daily. The focus of the present study was to analyze the reaction of gifted undergraduate students on social media during the quarantine period of the COVID-19. A special group of gifted students, who joined the program of attracting and nurturing talents at the University of Jeddah, University students as were the target sample of this study. To analyze online reactions during the pandemic; the choice of university students was arrived at as they are perceived to be gifted academically. Hence, the analysis of the impacts on their behavior on social media use is imperative. This study presented accurate and consistent data on the effects of social media using Twitter platforms on gifted students during the quarantine occasioned by the COVID-19 pandemic. The behavior of learners due to during the use of social media was extensively explored and results analyzed. The study was carried out between April and May 2020 (quarantine period in Saudi Arabia) to establish whether the online behavior of gifted students reflects positive or negative feelings. The methods used in conducting this study the research were online interviews and scraping participants' Twitter accounts (where most of the online activities and studies take place). The study employed the Activity theory to analyze the behavior of gifted students on social media. The sample size used was 60 students, and the analysis of their behavior was based on Activity theory Overall, the results showed proactive, positive behavior for coping with a challenging situation, educating society, and entertaining. Finally, this study recommends investing in gifted students due to their valuable problem-solving skills that can help handle global pandemics efficiently.