• 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.

• Journal of Distribution Science
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• v.17 no.3
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• pp.85-95
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• 2019

Purpose - The existing marketing studies using Social Network Analysis have assumed that network structure variables are time-invariant. However, a node's network position can fluctuate considerably over time and the node's network structure can be changed dynamically. Hence, if such a dynamic structural network characteristics are not specified for virtual goods purchase model, estimated parameters can be biased. In this paper, by comparing a time-invariant network structure specification model(base model) and time-varying network specification model(proposed model), the authors intend to prove whether the proposed model is superior to the base model. In addition, the authors also intend to investigate whether coefficients of network structure variables are random over time. Research design, data, and methodology - The data of this study are obtained from a Korean social network provider. The authors construct a monthly panel data by calculating the raw data. To fit the panel data, the authors derive random effects panel tobit model and multi-level mixed effects model. Results - First, the proposed model is better than that of the base model in terms of performance. Second, except for constraint, multi-level mixed effects models with random coefficient of every network structure variable(in-degree, out-degree, in-closeness centrality, out-closeness centrality, clustering coefficient) perform better than not random coefficient specification model. Conclusion - The size and importance of virtual goods market has been dramatically increasing. Notwithstanding such a strategic importance of virtual goods, there is little research on social influential factors which impact the intention of virtual good purchase. Even studies which investigated social influence factors have assumed that social network structure variables are time-invariant. However, the authors show that network structure variables are time-variant and coefficients of network structure variables are random over time. Thus, virtual goods purchase model with dynamic network structure variables performs better than that with static network structure model. Hence, if marketing practitioners intend to use social influences to sell virtual goods in social media, they had better consider time-varying social influences of network members. In addition, this study can be also differentiated from other related researches using survey data in that this study deals with actual field data.

• 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.

• The Journal of the Korea Contents Association
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• v.12 no.5
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• pp.370-379
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• 2012

This study is identifying a social standing on adolescents' social network in offline and how the social standing influence to online social activity. For the purpose, we explore two research questions. First, How the adolescents' social standing present in their offline social network? Second, How the adolescents' social standing influence to online social activity? Using data, we first visualized 5 social network of adolescents, and deducted each ego networks and global network. Also we investigated causality between social standing and social activities. The result showed adolescents' social tie and social gregariousness influence to social activity width and depth in ego network. Based on these findings, we discussed some implications, limitations, and future direction.

• Journal of the Korean Home Economics Association
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• v.30 no.3
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• pp.177-191
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• 1992

This study investigated how different relationships the family has with its social networks by social class. Among research families' primary social networks, the wife's relatives are the most, the neighbor the second, the husband's relative the third, and the church (or other religious groups) the fourth. Social class does not make any difference in what social network is the family's primary social network. When the husband or the wife participates in a social network, he or she tends to participate alone without his or her spouse. When the husband's educational level is high, the wife tends to participate in her alumni association alone. When the husband is in a professional or a white-collar occupation, he is likely to socialize with his work associates alone. On the contrary, when the family income gets high, the husband tends to bring his wife to his alumni association. When looking for a job, most husbands and wives do not resort to a social network for help. Lower-class people are more likely to obtain jobs through their social networks compared to higher-class people. That is, the lower one's educational levle, one's occupational status, or the family income is, the more likely one gets help from some social networks in searching jobs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3984-3996
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• 2014

Mobile social network can be seen as a specific application of the DTN (Delay Tolerant Network), in which the information propagation can be impacted by many social behaviors of the nodes. For a specific node, its social behaviors are various. For example, the node may not be interested in the information before receiving it and may also discard the information after getting it. On the other hand, people are more willing to forward the message to his friends. These interactive behaviors between nodes can be seen as social behaviors. It is easy to see that the impact of the social behaviors is related to the social ties, which can be manifested by the structure of the social network. State of the art works often simply assumes that the social networks can be divided into some communities. At present, some works find that the structure of some social networks is scale-free. To overcome this problem, this paper proposes a theoretical model to evaluate the impact of above social behaviors in the DTN-like scale-free network. Simulation shows the accuracy of the model. Numerical results show that both social behaviors and scale-free character have significant impact on information propagation. Moreover, the impact of social behaviors is related to the scale-free character of the networks.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.1
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• pp.50-70
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• 2013

The creation of new economic paradigm shift in creative economy age have influence on the characteristics of social networks and space, it leads to the formation of new relationship in space depending on social network service development. In this paper, it gives a name to 'social network resource' the power affecting these features and to find the meaning of spatial changes in the economic geography perspectives. 'Social network resource' shows the characteristics of openness, sharing, participation and cooperation, with features of encompassing all the features of local and global characteristics in space. This features are related the meaning of 'trans-locality' and can be found in the case of 'WikiSeoul.com (http:/www.wikiseoul.com)', Seoul's social knowledge sharing web platform. In particular, physical resources, human resources, information resources, and the characteristics of the relationship as a resource features was found and these features appear in space is projected to the space of social relations, it reflects the characteristics of qualitative space regarding social network resource.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1168-1188
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• 2018

Social Network Aggregators are used to maintain and manage manifold accounts over multiple online social networks. Displaying the Activity feed for each social network on a common dashboard has been the status quo of social aggregators for long, however retrieving the desired data from various social networks is a major concern. A user inputs the query desiring the specific outcome from the social networks. Since the intention of the query is solely known by user, therefore the output of the query may not be as per user's expectation unless the system considers 'user-centric' factors. Moreover, the quality of solution depends on these user-centric factors, the user inclination and the nature of the network as well. Thus, there is a need for a system that understands the user's intent serving structured objects. Further, choosing the best execution and optimal ranking functions is also a high priority concern. The current work finds motivation from the above requirements and thus proposes the design of a query processing system to retrieve information from social network that extracts user's intent from various social networks. For further improvements in the research the machine learning techniques are incorporated such as Latent Dirichlet Algorithm (LDA) and Ranking Algorithm to improve the query results and fetch the information using data mining techniques.The proposed framework uniquely contributes a user-centric query retrieval model based on natural language and it is worth mentioning that the proposed framework is efficient when compared on temporal metrics. The proposed Query Processing System to Retrieve Information from Social Network (QPSSN) will increase the discoverability of the user, helps the businesses to collaboratively execute promotions, determine new networks and people. It is an innovative approach to investigate the new aspects of social network. The proposed model offers a significant breakthrough scoring up to precision and recall respectively.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.261-269
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• 2012

The purpose of this study was to suggest policies that take advantage of social networking services in the field of social commerce. Presented it, in order for the concept of a social network service for the first time, were examined by four representative types of social network services, and analyzed the characteristics of each. Domestic current status and concepts presented and the addition of social commerce, and analyzed the characteristics of each type proposed six kinds. Utilizing social network services to the end, was to suggest measures that can be incorporated into the social commerce business. The results of this study suggested that the marketing implications for how social network services in the social commerce business that can be utilized in companies that will say that its worth.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.2
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• pp.19-27
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• 2011

Recent development of information technologies produces a lot of community services. Social Network Service is one of the community services on the world wide webs. In the Social Network Service, a user can register other users as friends and enjoy communication through a virtual message. Previous researches show a few social service methods using manually generated tagging. However, the manual social tagging is not widely used in many social network services. Moreover, they do not consider ubiquitous computing environment. We propose a recommendation method for social service using contexts in ubiquitous environment. Our method scores documents based on context tags and social network services. Our social scoring model is computed by both a tagging score of a document and a tagging score of a document that was tagged by a user's friends.