• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.443-461
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• 2014

Overlay routing has emerged as a promising approach to improve reliability and efficiency of the Internet. For one-hop overlay source routing, when a given primary path suffers from the link failure or performance degradation, the source can reroute the traffic to the destination via a strategically placed relay node. However, the over-heavy traffic passing through the same relay node may cause frequent package loss and delay jitter, which can degrade the throughput and utilization of the network. To overcome this problem, we propose a Load-Balanced One-hop Overlay Multipath Routing algorithm (LB-OOMR), in which the traffic is first split at the source edge nodes and then transmitted along multiple one-hop overlay paths. In order to determine an optimal split ratio for the traffic, we formulate the problem as a linear programming (LP) formulation, whose goal is to minimize the worse-case network congestion ratio. Since it is difficult to solve this LP problem in practical time, a heuristic algorithm is introduced to select the relay nodes for constructing the disjoint one-hop overlay paths, which greatly reduces the computational complexity of the LP algorithm. Simulations based on a real ISP network and a synthetic Internet topology show that our proposed algorithm can reduce the network congestion ratio dramatically, and achieve high-quality overlay routing service.

• Health Communication
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• v.12 no.1
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• pp.51-72
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• 2017

Purpose: Adolescents use emoticons to express their emotions in an online environment. Hence, medical experts can understand the emotions of adolescents by emoticons. The goal of this study was to investigate the relationship between various emotions and emoticons among the Korean adolescents. Methods: The questionnaire survey was conducted between September 1 and 30, 2014, involving 3,272 students in elementary schools, middle schools, and high schools affiliated in the Department of Education of the metropolitan city of Busan. A total of 1,717 students responded to the survey. The participants consisted of 806 males (46.9%), and 911 females (53.1%). Among these, there were 557 elementary school students (32.4%), 617 middle school students (35.9%), and 543 high school students (31.6%). A social networking analysis was conducted using NodeXL. Results: The frequency of emoticon use among adolescents runs in the order of joy, sadness, fear, surprise, anger, disgust, and then depression. Elementary school females mainly use emoticons to express joy; middle school females use emoticons to express sadness, surprise, anger, disgust, and depression; and high school females use emoticons to express fear. Age- and gender-specific emoticon networks were visualized by using the Haren-Korel fast multiscale algorithm. Commonly used emoticons by age and gender were expressed in the networks. Results of age- and gender-specific emoticon networks visualization show similar results of centrality of seven emoticons. Conclusion: In the digital communication environment, emoticons could be used to catch the emotions of adolescents in Korea.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.1
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• pp.15-22
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• 2014

Delay-Tolerant Network employs message forwarding based on a Store, Carry and Forward method to conquer no guarantee of continue connectivity. For this reason, a lot of DTN routing scheme have been proposed recently. message forwarding is an important research issue in delay-tolerant network and In this paper, we propose a efficiency DTN routing scheme using node's social relation and expanded Ego-network betweenness centrality. Our simulation results show that it is more efficient to message delivery cost than Epidemic routing, Friendship routing while it has a little performance degradation of message delivery ratio.

• Journal of Korean Academy of Nursing
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• v.46 no.1
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• pp.50-58
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• 2016

Purpose: The purpose of this study was to identify the knowledge structure of cancer survivors. Methods: For data, 1099 articles were collected, with 365 keywords as a Noun phrase extracted from the articles and standardized for analyzing. Co-occurrence matrix were generated via a cosine similarity measure, and then the network analysis and visualization using PFNet and NodeXL were applied to visualize intellectual interchanges among keywords. Results: According to the result of the content analysis and the cluster analysis of author keywords from cancer survivors articles, keywords such as 'quality of life', 'breast neoplasms', 'cancer survivors', 'neoplasms', 'exercise' had a high degree centrality. The 9 most important research topics concerning cancer survivors were 'cancer-related symptoms and nursing', 'cancer treatment-related issues', 'late effects', 'psychosocial issues', 'healthy living managements', 'social supports', 'palliative cares', 'research methodology', and 'research participants'. Conclusion: Through this study, the knowledge structure of cancer survivors was identified. The 9 topics identified in this study can provide useful research direction for the development of nursing in cancer survivor research areas. The Network analysis used in this study will be useful for identifying the knowledge structure and identifying general views and current cancer survivor research trends.

• Korean Association of Arts Management
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• no.57
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• pp.59-84
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• 2021

This study examined the structure of YouTube video network and the factors for the diffusion of Chinese creator's videos through the case of famous Chinese creator Fengtimo. There is few interest to the diffusion of Chinese contents among Korean researchers, while they have been studied the consumption of Hallyu(Korean wave) contents overseas. Using the data that YouTube Data API offers, this study analysed the video network that the comments of which are same users with NodeXL tools and the regression model with JASP tools. The study found that there are three groups of the YouTube channels of that network. They are domestic official accounts of Fengtimo, foreign officail accounts of Fengtimo and individual creators' accounts. The official accounts share the videos of Fengtimo's songs and entertainment contents for the fans, where the individual creators share their own meme videos(UGC). The significant factors for the diffusion in the YouTube video network are comments, likes, out-degree, dislikes, in-degree and betweenness centrality. There are significant difference between official channel and indivisual groups on the views. And degree and betweenness centrality have mediating effect. It is necessary to conduct more research on that subject with many other cases if we want to get to know the generalized explanation.

• 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.

• The Research Journal of the Costume Culture
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• v.27 no.4
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• pp.299-309
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• 2019

Citation frequency is an important factor in evaluating journal quality and is used as a measure of journal impact. The citation index of a paper plays an important role in linking papers with groups of other academic papers, forming a huge and complex network. This study examines the intellectual structure of apparel research through the bibliometric citation analysis of The Research Journal of the Costume Culture (RJCC). In order to analyze the changes in the intellectual structure of the RJCC, we used the Korea Citation Index's (KCI) data (highly citing journals and highly cited journals). The NodeXL, a social network analysis tool, was used to examine the connection structure between journals. In order to identify the academic influence of the RJCC, we used the KCI journal citation index. Our findings indicate that the RJCC has a high centrality index among the clothing-oriented journals in the same life sciences field. A look at the journals citing the RJCC and the journals cited within the RJCC also showed that more journals of diverse fields have been recently linked through their citations. This suggests that a convergence of interdisciplinary research is underway in the field of clothing. As a result of examining international journals cited in the RJCC, it was confirmed that they were cited in prominent international journals in various fields.

• The Research Journal of the Costume Culture
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• v.27 no.3
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• pp.193-205
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• 2019

A trend analysis of research articles in a field of knowledge is significant because it can help in finding out the structural characteristics of the field and the future direction of research through observing change in a time series. We identified the structural characteristics and trends in text data (keywords) gathered from research articles which in itself is an important task in various research areas. The titles and keywords were crawled from research articles published from 2016 to 2018 in the Research Journal of the Costume Culture (RJCC), one of the representative Korean journal in the field of clothing and textile. After we extracted data comprising English titles and keywords from 195 published articles, we transformed it into a 1-mode matrix. We used measures from network analysis (i.e., link, strength, and degree centrality) for evaluating meaningful patterns and trends in the research on clothing and textile. NodeXL was used for visualizing the semantic network. This study observed change in the clothing and textile research trend. In addition to covering the core areas of the field, the subjects of research have been diversifying with every passing year and have evolved onto a developmental direction. The most studied area in articles published by the RJCC was fashion retailing/consumer psychology while aesthetic/historic and fashion industry/policy studies were covered to a more limited extent. We observed that most of the studies reflecting the identity of RJCC share subject keywords to a significant extent.

• Radiation Oncology Journal
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• v.28 no.3
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• pp.184-191
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• 2010

Purpose: To evaluate the structural characteristics of a scientific network of radiation oncology society. Materials and Methods: A total of 1,512 articles published from 1986 to April 2010 with the terms 'radiation oncology' or 'therapeutic radiology' were obtained in the KoreaMed database. The co-authors were analyzed according to their affiliation, and their relationship was used to build a matrix. With the matrix, centralization indices and the Key Player index were analyzed. We used UCINET 6.0 for the network analysis, Netdraw for determining a sociogram and Key Player 1.44 for the key player analysis. Results: The centralization of the radiation oncology field decreased from 8.29% for the period from 1986~1990 to 1.84% from 2006~2010. However, when the Korean Journal of Medical Physics was excluded, centralization increased from 2.32% for the period from 2001~2005 to 3.80% from 2006~2010. This suggested that the communication in the clinical research field of radiation oncology is decreasing. In a node centralization analysis, Seoul National University was found to be the highest at 7.9%. Seoul National University showed the highest indices in the Outdegree (6.50%) and Indegree (8.54%), in addition to Betweenness (14.94%) and Eigenvector (135.234%). The Key Player analysis indicated that Inha University had the highest index at 0.491, but when the Korean Journal of Medical Physics was excluded, Yonsei University had the highest Key Player index at 0.584. Conclusion: The degree centrality in the network of radiation oncology decreased in the most recent period as more institutions are participating in network. However, the Betweenness centrality is still increasing, suggesting that the communications among research groups (clique) in radiation oncology is warranted.