• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3203-3215
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• 2015

Due to the high growth of SNS population, service scalability is one of the critical issues to be addressed. The cloud environment provides the flexible computing and storage resources for services deployment, which fits the characteristics of scalable SNS deployment. However, if the SNS related information is not properly placed, it will cause unbalance load and heavy transmission cost on the storage virtual machine (VM) and cloud data center (CDC) network. In this paper, we characterize the SNS into a graph model based on the users' associations and interest correlations. The node weight represents the degree of associations, which can be indexed by the number of friends or data sources, and the link weight denotes the correlation between users/data sources. Then, based on the SNS graph, the two-step algorithm is proposed in this paper to determine the placement of SNS related data among VMs. Two k-means based clustering schemes are proposed to allocate social data in proper VM and physical servers for pre-configured VM and dynamic VM environment, respectively. The experimental example was conducted and to illustrate and compare the performance of the proposed schemes.

• Journal of Digital Convergence
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• v.9 no.4
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• pp.235-244
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• 2011

According to spread of Smart Work introduction to public organizations & commercial enterprises, its being more focused on how to implement Smart Work effectively. So far current Smart Work, mainly Mobile Office has emphasized the speed & efficiency of management. But future Smart Work, Smart Work 2.0 must focus on the creativity & innovation of companies & people. In order to do that, the new technology like Social networking & Cloud computing should be applied. This study suggests Smart Work 2.0 implementation methodology including critical successful factors & solutions of Smart Work implementation through referencing existing implementation methodology and case study.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.83-89
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• 2016

This study aimed to examine how gender and regional differences affect the relationships between SNS use and social capital. By analyzing a large set of data from Korean teenagers, significant roles of gender and regional differences could be found. In regards to gender difference, the most notable finding was the negative effects of SNS use on bonding and bridging social capital among male teenagers. Furthermore, it was found that such negative effects of SNS use were significant particularly among urban teenagers. These findings theoretically contribute to broadening the understanding of the relationships between SNS use and social capital.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.119-125
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• 2020

Based on an online experiment, this research examined how uncivil expressions made by participants from the same political partisan group (in-group) influenced the emotional and behavioral intentions of other in-group members, especially when the incivility was supported by social recommendations such as "recommendations." As predicted, results showed that a higher level of vicarious shame was felt when participants perceived higher levels of incivility. However, no significant effects of social recommendations were found regarding levels of vicarious shame. That is, the level of shame was not significantly different between participants who were exposed to an in-group uncivil comment that received recommendations and participants who were exposed to in-group uncivil comment without recommendations. Findings further found two types of coping strategies -situation-reparation and situation-avoidance - among participants exposed to in-group uncivil comments. Yet no significant effects were found regarding coping strategies in response to the presence of social recommendations. Participants' feelings of shame were positively correlated with both types of coping strategies, supporting findings of previous studies. Implications of this study are further discussed.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.40-45
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• 2015

Online social networks(OSN) are very popular nowadays. As OSNs grows, the commercial markets are expanding their social commerce by applying Influence Maximization. However, in reality, there exist more than two players(e.g., commercial companies or service providers) in this same market sector. To address the Influence Maximization problem between adversaries, we first introduced Influence Maximization against the social adversaries' problem. Then, we proposed an algorithm that could efficiently solve the problem efficiently by utilizing social network properties such as Betweenness Centrality, Clustering Coefficient, Local Bridge and Ties and Triadic Closure. Moreover, our algorithm performed orders of magnitudes better than the existing Greedy hill climbing algorithm.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.153-158
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• 2016

As the number of social network users increases, the information on event such as social issues and disasters receiving attention in each region is promptly posted by the bucket through social media site in real time, and its social ripple effect becomes huge. This study proposes a detection method of events that draw attention from users in specific region at specific time by using twitter data with regional information. In order to collect Twitter data, we use Twitter Streaming API. After collecting data, We implemented event detection system by analyze the frequency of a keyword which contained in a twit in a particular time and clustering the keywords that describes same event by exploiting keywords' co-occurrence graph. Finally, we evaluates the validity of our method through experiments.

• Journal of Internet Computing and Services
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• v.17 no.2
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• pp.97-107
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• 2016

The purpose of this study was to investigate the determinant factors of the social capital construction through socal media focused on social media use, motives, trust. Total of 261, college students participated in this study. The data were analyzed by the exploratory factor analysis, confirmatory factor analysis, correlation analysis, reliability analysis and path analysis based on structural equation model analysis using IBM SPSS 21 and IBM AMOS 21 program. Results show that social media use, motives(employment/reminiscences) and social media trust influenced positively on bridging social capital. Second, motives of use(information/exchange) and social media trust influenced positively on bonding social capital. Finally, social media use, specifically, social media trust generally promotes participatory social capital.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.101-112
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• 2017

The purpose of this study was to examine the factors affecting innovation resistance and intention of use of social TV non-users focused on innovation diffusion theory and innovation resistance model. The results were as follows: First, compatibility among perceived innovation characteristics by social TV non-users influenced negatively on innovation resistance, and complexity among perceived innovation characteristics by social TV non-users influenced positively on innovation resistance. Second, perceived risk by social TV non-users influenced positively on innovation resistance. Third, compatibility among perceived innovation characteristics by social TV non-users influenced positively on social TV intention to use. And complexity among perceived innovation characteristics by social TV non-users influenced negatively on social TV intention to use. Fourth, perceived risk by social TV non-users influenced not significantly on social TV intention to use. Fifth, innovation resistance by social TV non-users influenced negatively on social TV intention to use.

• The Journal of the Korea Contents Association
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• v.17 no.7
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• pp.93-100
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• 2017

Recently, demands for high-performance flash-based storage devices (i.e., flash SSD) have rapidly grown in social network services, cloud computing, super-computing, and enterprise storage systems. The industry and academic communities made the NVMe specification for high-performance storage devices, and NVMe-based flash SSDs can be now obtained in the market. In this article, we evaluate performance of NoSQL databases that social network services and cloud computing services heavily adopt by using NVMe-based flash SSDs. To this end, we use NVMe SSD that Samsung Electronics recently developed, and the SSD used in this study has performance up to 3.5GB/s for sequential read/write operations. We use WiredTiger for NoSQL databases, and it is a default storage engine for MongoDB. Our experimental results show that log processing in NoSQL databases is a major overhead when high-performance NVMe-based flash SSDs are used. Furthermore, we optimize components of log processing and optimized WiredTiger show up to 15 times better performance than original WiredTiger.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.432-436
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• 2010

Finding communities from network data including social networks can be done by clustering the nodes of the network as densely interconnected groups, where keeping interconnection between groups sparse. To exploit a clustering algorithm for community detection task, we need a well-defined similarity measure between network nodes. In this paper, we propose a new similarity measure named "Common Neighborhood Sub-graph density" and combine the similarity with affinity propagation, which is a recently devised clustering algorithm.