• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.6
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• pp.485-491
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• 2013

Recently, with the proliferation of social network services, users and many companies hope that their information spread more faster. In order to study the information diffusion in the social networks, many algorithms such as greedy algorithm and heuristic algorithm have been proposed. However, the greedy algorithm is too complicated to use in real-life social network, and the heuristic algorithms have been studied under the uniform distribution of diffusion probability, which is different from the real social network property. In this paper, we propose an heuristic information diffusion maximization algorithm based on diffusion probability and node degree. For performance evaluation, we use real social network database, and it is verified that our proposed algorithm activates more active nodes than existing algorithms, which enables faster and wider information diffusion.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.5
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• pp.209-216
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• 2013

In traditional social network analysis, the betweenness centrality measure has been heavily used to identify the relative importance of nodes in terms of message delivery. Since the time complexity to calculate the betweenness centrality is very high, however, it is difficult to get it of each node in large-scale social network where there are so many nodes and edges. In this paper, we define a new type of network, called the expanded ego network, which is built only with each node's local information, i.e., neighbor information of the node's neighbor nodes, and also define a new measure, called the expended ego betweenness centrality. Through the intensive experiment with Barab$\acute{a}$si-Albert network model to generate the scale-free networks which most social networks have as their embedded feature, we also show that the nodes' importance rank based on the expanded ego betweenness centrality has high similarity with that based on the traditional betweenness centrality.

• Asia pacific journal of information systems
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• v.29 no.3
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• pp.382-406
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• 2019

We study the antecedents to tie formation on an (Facebook-like) enterprise social media platform implemented to support cross-boundary connections. Research has produced mixed findings regarding the role of social media in cultivating bridging vs. closed networks. We examine the tie formation patterns of 1,386 enterprise social media users over a two-year period. Specifically, we observe who became (or chose not s become) "friends" with whom at the dyadic level and relate the decisions to various mechanisms that affect one's network to expand, constrain, or bridge. Using logistic and OLS regressions, we find that users tend to form ties via reciprocity and transitivity (with friends of friends), both of which help expand one's network. We also find strong networking tendency toward functional and hierarchical homophily (same business unit and same rank, respectively), which is likely to constrain one's network (closed network structure). We find that one's participation in various online interest groups is likely to open one's network (bridging network structure) while no evidence found for preferential attachment. Overall, we find that enterprise social media offers features, some of which are likely to foster bridging while others foster closed networks via different mechanisms.

• The Journal of Information Systems
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• v.21 no.4
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• pp.1-29
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• 2012

The purpose of this study was to find about personal information security of internet and social networks by focusing on end users. User competence and subjective criterion, which are the antecedents, are affecting security behaviors For these security behaviors, the study examined the relationship between security behavior intention on internet use and security behavior intention about social network that is actively achieved in many fields. Behaviors of internet and social network were classified into an action of executing security and an action of using a security technology. In addition, this study investigated a theory about motivational factors of personal intention on a certain behavior based on theory of reasoned action in order to achieve the purpose of this study. A survey was conducted on 224 general individual users through online and offline, and the collected data was analyzed with SPSS 12.0 and SmartPLS 2.0 to verify demographic characteristics of respondents, exploratory factor analysis, and suitability of a study model. Interesting results were shown that security behavior intention of social network is not significant in all security behavior execution, which is security performance behavior, and security technology use. Internet security behavior is significant to security technology use but it does not have an effect on behavior execution.

• Journal of Information Technology Applications and Management
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• v.23 no.2
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• pp.207-224
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• 2016

Investments in information and communication technologies (ICT) around the world have grown at an enormous rate over the past two decades, which reflects a new emphasis on consumer mobile devices. A social network service (SNS) is an online service that aims to build social relations among people who share interests and activities. The role of SNS is enormous for communicating ideas and opinions among social participants. The use of SNS has recently become one of the most popular social activities worldwide. This research investigated relation between personal characteristics, social characteristics and user satisfaction on SNS then, analyzed how these factors affecting continuance usage intention on SNS users. The conclusion is summarized as below. The study results show that informativeness, pleasure, innovativeness, relationship and empathy of SNS are having positive impact to some degree on the user satisfaction. Further, the user satisfaction of SNS users and quality of life have a positive impact on the continuance usage intention of SNS users. This results show that various SNS qualities are necessary to actively explore and obtain further information that users intend to find, while they are insufficient in function to provide the information other users require or exchange information with other users through the SNS.

• Journal of Korean Library and Information Science Society
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• v.34 no.4
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• pp.1-20
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• 2003

Through analyzing papers on digital libraries and the contexts of usage of the term, ‘digital library’, this study investigates that the professional discourses about digital libraries regard them digital technologies. But digital libraries need to be recognized as socio-technical networks which are constructed by social interaction between heterogeneous elements. The study suggested that Social Informatics and a STIN(Socio-Technical Interaction Network) model should be applied to understand and analyze digital libraries as socio-technical networks.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.163-177
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• 2021

Many methods of discovering social networking communities or clustering of features are based on the network structure or the content network. This paper proposes a community discovery method based on topic models using a time factor and an unsupervised clustering method. Online community discovery enables organizations and businesses to thoroughly understand the trend in users' interests in their products and services. In addition, an insight into customer experience on social networks is a tremendous competitive advantage in this era of ecommerce and Internet development. The objective of this work is to find clusters (communities) such that each cluster's nodes contain topics and individuals having similarities in the attribute space. In terms of social media analytics, the method seeks communities whose members have similar features. The method is experimented with and evaluated using a Vietnamese corpus of comments and messages collected on social networks and ecommerce sites in various sectors from 2016 to 2019. The experimental results demonstrate the effectiveness of the proposed method over other methods.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.222-230
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• 2021

The article reviews the issue of formation of information culture of social work bachelors in the process of their professional training. The main internal / external factors that determine the need for the information culture formation of social workers-to-be have been identified. To determine the levels of information culture formed in bachelors of social work criteria and their indicators have been substantiated. The model of information culture formation in BSW has been developed and implemented in Ukrainian universities under the following pedagogic conditions: organized informational environment; interconnection between general and professionally-directed courses; curriculum includes course directed on IC formation. The model contained interconnected components: aim - to achieve higher level of information culture formed; specific principles; content, interactive methods and forms of organization of educational process, methods of control and correction; components of information culture. The implemented mastered learning procedure has contributed to the leveling up of information culture formed in social work bachelors.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.113-119
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• 2020

Numerous tourist-related data produced on the Internet contain not only simple tourist information but also diverse ideas and opinions from users. In order to derive meaningful information about tourist sites from such big data, the social network analysis of tourist keywords can identify the frequency of keywords and the relationship between keywords. Thus, it is possible to make recommendations more suitable for users by utilizing the clear recommendation criteria of tourist attractions and the relationship between tourist attractions. In this paper, a recommendation system was designed based on tourist site information through big data social network analysis. Based on user personality information, the types of tourism suitable for users are classified through deep learning and the network analysis among tourist keywords is conducted to identify the relationship between tourist attractions belonging to the type of tourism. Tour information for related tourist attractions shown on SNS and blogs will be recommended through tagging.

• 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.