• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.139-142
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• 2005

Recently research interest in Knowledge Management (KM) has grown rapidly. Companies regard intellectual capital as important asset and strive to deploy KM in an organization to gain a competitive edge. Many organizations currently engage in knowledge management in order to leverage knowledge both within their organization and externally to their shareholders and customers. Most of the previous research related to KM are dedicated to investigate the role of information technology in extracting, capturing, sharing, coverting organizational knowledge. Knowledge workers, however, are paid less attention though they are the key players in KM activities such as knowledge creation, dissemination, capture and conversion. We regard knowledge workers as a major component of KM and starting point of understanding organizational knowledge activities. Therefore we adopt a method to understand and analyze knowldge workers' social relationships. In this paper we investigate Social Network Analysis (SNA) as a tool for analyzing knowledge network. We introduce the basic concept of SNA and suggest a framework for implementing knowledge network by explaining how SNA can be used for analyzing knowledge network. We also propose a numerical method for identifying knowledge workers using SNA after classifying knowledge workers. The suggested method is expected to help understanding key knowledge players within an organization.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.268-271
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• 2009

In this paper, we analyze social network status and suggest TV SNS Service. According to alexa.com's recent chart, there are three SNS sites (facebook, myspace, twitter) in global top 20 sites. SNS usage has increased dramatically. Recently many SNS are growing up by opening their platform that make it easy to develope new services and functions by third party developers. KT is implementing open platform that is support Widget and SNS service. And Recently Social TV comes into the spotlight. Social TV is combination of social media and TV contents. It is enable to exchange emotion and opinion by communication with other people when watching Video contents. We propose TV SNS Service that provides various services by using advantage of SNS system and Social TV.

• Journal of Information Technology and Architecture
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• v.11 no.4
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• pp.471-483
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• 2014

The purpose of this study was to look over the sharing and flow of information on tourism tourist destination made through social media by utilizing social network analysis. In this research for compared the exchange and diffusion relationships and made information sharing among users of the network group for the Seoul / Busan Tourism Twitter. The first part of analysis dealt with the network centralization and information dissemination patterns from a global perspective. The second part was an analysis of nodes with the highest degree centrality in order to identify the most influential user within the Twitter network and determine the information flow and user characteristics with respect to the information dissemination pattern in Seoul/Busan tourism Twitter. The results scientific evidence was presented that social media users' information search behavior information to understand the sharing and spreading patterns, social media as a marketing tool, simple products and services that will ultimately provide the desired information detainee information is not a means of promoting utilization was presented.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.3
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• pp.31-38
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• 2013

The evolution of the Web from Web 1.0 to Web 2.0 has brought up new platforms as SNSs(Social Network Service) that are used by users to articulate and manage their relationships. SNSs are an online phenomenon which has become extremely popular. A SNS essentially consists of a representation of each user, his/her social links, and a variety of additional services. SNSs are increasingly attracting the attention of academic and industry researchers. What makes SNS unique is that they have a relationship with friends. The friend recommendation is one important feature of social networking services. People tend to trust the opinions of friends they know rather than the opinions of strangers. In this paper, we propose an efficient data processing method for social data. We study previous researches about social score in social network service. Our ESS(Efficient Social Score) is computed by both friendship weight and score of a document that was tagged by a user's friends. Our experimental results also confirm that our method has good performance.

• Journal of the Korean association of regional geographers
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• v.12 no.2
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• pp.245-264
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• 2006

According to many conceptual researches and discourses, development of information-communication technology(ICT) has made great influences upon activities on time and space. But some empirical studies have shown that its influence in the real world is not so great as we may expect In order to avoid these two oppositional views, this paper wants to put interests on socio-spatial relationships or networks, rather than individual phenomena or consciousness, which have been transformed under the influence of ICT. The development of ICT presupposes a creation of information network, and hence the term 'etwork social space' can be used to see its spatial influence, which would be further understood with the theory of actor-network. This paper also suggests that network social space has three strata, that is, 'nstant' 'unctional 'and 'aterial' and that network social space can be emphasized not only as newly emerging social space but also as reconstruction of subjects' identity through his/her participation into information network as its node.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1087-1101
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• 2013

Most people are connected to Social Network Services (SNS) through smart devices. Social Network Services are tools that transport information fast and easily. It does not care where he or she comes from. A lot of information circulates and is shared on Social Network Services. but Social Network Services faults are magnified and becoming a serious issue. For instance, malicious users generate multiple IDs easily on Facebook and he can use personal information of others on purpose, because most people tend to undoubtedly accept friend requests. In this paper, we have specified research scope to Facebook, which is one of most popular Social Network Services in the world. We propose a way of minimizing the number of malicious actions on Facebook from malignant users and malicious bots by setting criteria and applying reputation system.

• The Journal of Information Systems
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• v.32 no.2
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• pp.177-190
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• 2023

Purpose Recently, as a new business marketing tool, short form content focused on fun and interest has been shared as hashtags. By extracting positive and negative keywords from media audiences through comment analysis of social media news, various stakeholders aim to quickly and easily grasp users' opinions on major news. Design/methodology/approach YouTube videos were searched using the YouTube Data API and the results were collected. Video comments were crawled and implemented as HTML elements, and the collection results were checked on the web page. The collected data consisted of video thumbnails, titles, contents, and comments. Comments were word tokenized with the R program, comparing positive and negative dictionaries, and then quantifying polarity. In addition, social network analysis was conducted using divided positive and negative comments, and the results of centrality analysis and visualization were confirmed. Findings Social media users' opinions on issue news were confirmed by analyzing and visualizing the centrality of keywords through social network analysis by dividing comments into positive and negative. As a result of the analysis, it was found that negative objective reviews had the highest effect on information usefulness. In this way, previous studies have been reaffirmed that online negative information has a strong effect on personal decision-making. Corporate marketers will analyze user comments on social network services (SNS) to detect negative opinions about products or corporate images, which will serve as an opportunity to satisfy customers' needs.

• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.683-690
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• 2009

Social Networks which is composed of network with an individual in the center in a web support mutual-understanding of information by searching user profile and forming new link. Therefore, if we apply the Social Network which consists of web users who have similar immanent information to web search, we can improve efficiency of web search and satisfaction of web user about search results. In this paper, first, we make a Social Network using web users linked directly or indirectly. Next, we calculate Similarity among web users using their immanent information according to topics, and then reconstruct Social Network based on varying Similarity according to topics. Last, we compare Similarity with Search Pattern. As a result of this test, we can confirm a result that among users who have high relationship index, that is, who have strong link strength according to personal attributes have similar search pattern. If such fact is applied to search algorithm, it can be possible to improve search efficiency and reliability in personalized and social search.

• The Journal of Information Systems
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• v.21 no.4
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• pp.109-132
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• 2012

Social Network Analysis is an increasingly important part of a broader 'toolbox' of evaluation methods available to R&D policymakers to support decision-making. The aim of this research is to be an accessible, 'beginner's guide' to social network theory and application in the area of mobile telecommunication research and development (R&D) decision-making. This research suggests the methodology of investigation into new technology, and the methodology suggested by this research is believed to be a meaningful first step toward the establishment of the information analysis structure, which is in desperate need.

• ETRI Journal
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• v.34 no.4
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• pp.591-601
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• 2012

Unstructured peer-to-peer (p2p) networks usually employ flooding search algorithms to locate resources. However, these algorithms often require a large storage overhead or generate massive network traffic. To address this issue, previous researchers explored the possibility of building efficient p2p networks by clustering peers into communities based on their social relationships, creating social-like p2p networks. This study proposes a social relationship p2p network that uses a measure based on Hebbian theory to create a social relation weight. The contribution of the study is twofold. First, using the social relation weight, the query peer stores and searches for the appropriate response peers in social-like p2p networks. Second, this study designs a novel knowledge index mechanism that dynamically adapts social relationship p2p networks. The results show that the proposed social relationship p2p network improves search performance significantly, compared with existing approaches.