• The Journal of Information Systems
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• v.22 no.1
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• pp.65-87
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• 2013

The development and expansion of communication technology in the field of information technology (IT) have changed the method and culture of communication, mediating communication among people. In particular, since social network service (SNS) has the attributes of information delivery and processing, it has a more powerful dissipating effect and influence than other existing communication methods. The role of users in SNS is important because it has the communication structure of producer-consumer, which consists of sharing, connection and participation of users. In this line, the purpose of this study is to investigate the intention for continued use of SNS by user ability. In order to explain the motivation and behavior for continued use of SNS by users, this study employed the motivation theory and post-adaptation model. The study applied 'media literacy' to the characteristics of SNS media and environment and expanded it into the concept of 'SNS literacy' to identify the moderating effect by user ability. Referred to as 'user's ability that is required to use SNS,' the SNS literacy was verified for its moderating effect with the three sub-dimensions: 'technical accessing ability,' 'understanding ability' and 'creative ability.' The major findings of this study are as follows. First, the perceived usefulness and playfulness were found to have a significant effect on the intention for continued use of SNS, showing the same result with previous studies on technology acceptance. In other words, usefulness and playfulness are variables with an explanatory power in the SNS environment as well. Second, the conceptualization of SNS literacy with accessing ability, understanding ability and creative ability was found to be valid. Third, it was verified that there was a significant difference in the SNS literacy between perceived usefulness and continued use, indicating that users with higher ability respond sensitively to usefulness and affect continued behavior. The moderating effect of SNS literacy was also verified in the relationship between perceived playfulness and intention for continued use. The results above confirm the difference in post-adaptation behavior of individuals, and are expected to provide several implications.

• Information Systems Review
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• v.13 no.3
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• pp.1-14
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• 2011

In recent years, SNS (Social Network Service) has spread globally and general corporate' utilization of SNS is gradually increasing. Accordingly, the scope of utilizing SNS is expanding not only as a simple publicity of products and services but also as a communication tool among the company members, the customer service and the product development, etc. This study is examining the related cases classified by the premier activities and the supportive activities of the private companies' viewpoints of utilizing the SNS. Based on this study results, we are proposing the strategic considerations for the private companies' SNS adoption by synthesizing the results of the analytical researches of the SNS cases that support the companies' value chain and the considerations of companies' utilization of the SNS that are proposed by the various private companies' research laboratories.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.24-38
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• 2018

Since a social networking service (SNS) isconsidered as an effective means to communicate and interact with customers, companies are trying to utilize SNS effectively. There is a lack of theory relating to the attributes of SNS. This study aims to investigate the attributes of SNS to classify SNS. Based on the social network theory, and previous studies on internet, blog, homepage, communication attributes, this study proposes the seven attributes to classify SNS: interaction, communication, entertainment, information, sharing, intimacy and connection. A pre-test, a pilot test and a main test are conducted. In the main test, 239 SNS users are participated. Through a factor analysis this study verifies the seven attributes of SNS. An analysis of variance with multiple comparisons of $Scheff{\acute{e}}$ method identifies that three attributes, interaction, communication and connection, are found to play significant roles to differentiate SNS. Looking at the overall mean values of the SNS by attribute, interaction, sharing, entertainment, intimacy and communication were relatively high in Facebook. Facebook showed higher values in attributes of interaction, sharing, entertainment, intimacy and communication. Twitter shows the relatively high scores for information and connection. Regarding interaction, Facebook shows higher scores than Twitter and Cyworld. For connection, Cyworld showed a significantly lower score than Twitter and Facebook. Cyworld was separated from the others in the light of communication. Cyworld is relatively weak in communication as it is limited to the message exchanges. The results will help in identifying major attributes for each SNS and classifying SNS.

• The Journal of Information Systems
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• v.22 no.3
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• pp.1-24
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• 2013

SNS(Social Network Services) is being recognized as an important part in our society, individual lives and corporate business aspects, and the influence of SNS is growing explosively as expansion and supply of infrastructures that support mobile environments increase. Previous studies related to SNS were focused on user acceptance of new technology, based on Technology Acceptance Model(TAM). However, they had a limitation to focus on technology acceptance, without the consideration of personal and behavioral factors in SNS use. However, above all, successful SNS requires the understanding of users who are active on the network. Therefore, from the user's perspective, this study attempted a multi-dimensional approach by reflecting characteristics that come from SNS usage. This study considered user innovation, virtual skill, self-efficacy, social pressure and network effect as independent variables, and perceived ease-of-use, perceived usefulness and perceived value as mediating variables, and intention-to-use as dependent variable. The result showed that user innovation, self-efficacy, social pressure and network effect had a significant effect on the mediating variables. The practical contribution of this study is to suggest useful decision alternatives concerned to marketing strategy for acquiring and retaining lone-term customers related to SNS business.

• 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 Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• 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 the Korea Society of Computer and Information
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• v.23 no.7
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• pp.19-26
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• 2018

This paper presents a structuring process of unstructured social network service (SNS) messages on rail services. We crawl messages about rail services posted on SNS and extract keywords indicating date and time, rail operating company, station name, direction, and rail service types from each message. Among them, the rail service types are classified by machine learning according to predefined rail service types, and the rest are extracted by regular expressions. Words are converted into vector representations using Word2Vec and a conventional Convolutional Neural Network (CNN) is used for training and classification. For performance measurement, our experimental results show a comparison with a TF-IDF and Support Vector Machine (SVM) approach. This structured information in the database and can be easily used for services for railway users.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.275-285
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• 2014

The development of ICT has promoted the infusion of 'social,' which is not only 'personal,' but also strengthens social connection and communication; and SNS lies in the center of the infusion. Although SNS has been positioning itself as a significant domain in our lives based on the developed technologies, such as openness, extendibility and real-time, it has caused social concerns due to unexpected side effects. Therefore, this study aims to identify the stressors causing SNS stress and the factors influencing discontinuance of SNS. As a result, 5 factors including 'techno-overload,' 'techno-invasion,' 'techno-insecurity,' 'techno-complexity' and 'pace of change' were found to be SNS stressors. It is thought that this study would provide an academic implication for the future studies of stress and discontinuance related to SNS and a guideline for establishing practical strategies.

• Knowledge Management Research
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• v.15 no.2
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• pp.1-21
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• 2014

In this study we adopted Interpersonal Process Model of Intimacy to study SNS use intention. First, we investigated the effects of personal identity, social identity and intimacy. Second, we tested the influences of self-disclosure, partner disclosure on perceived partner responsiveness. Third, we measured the relationship between perceived partner responsiveness and intimacy. Lastly, we investigated the effects of intimacy, perceived partner responsiveness and use intention. A total of 232 final respondents were collected from users of Social Network Services in 2011. The results revealed several important findings. First, we found that social identity had a significant and positive effect on intimacy. However, personal identity showed insignificant effect toward intimacy. Moreover, self-disclosure and partner disclosure had a positive effects on perceived partner responsiveness. perceived partner responsiveness showed a positive effect on both intimacy and use intention. Lastly, intimacy had significant effect on use intention.