• 유통과학연구
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• 제17권3호
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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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• 제15권11호
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• pp.3935-3949
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• 2021

With the rapid development of Internet and big data technology, various online social network platforms have been established, producing massive information every day. Hot topic discovery aims to dig out meaningful content that users commonly concern about from the massive information on the Internet. Most of the existing hot topic discovery methods focus on a single network data source, and can hardly grasp hot spots as a whole, nor meet the challenges of text sparsity and topic hotness evaluation in cross-network scenarios. This paper proposes a novel hot topic discovery method across social network based on an im-proved LDA model, which first integrates the text information from multiple social network platforms into a unified data set, then obtains the potential topic distribution in the text through the improved LDA model. Finally, it adopts a heat evaluation method based on the word frequency of topic label words to take the latent topic with the highest heat value as a hot topic. This paper obtains data from the online social networks and constructs a cross-network topic discovery data set. The experimental results demonstrate the superiority of the proposed method compared to baseline methods.

• 여성건강간호학회지
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• 제9권1호
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• pp.50-60
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• 2003

Purpose : The purpose of this study was to evaluate the factors which are related to the maternal role performance of first-time mother to improve the health of infant. Specifically a basic hypothetical model was developed based on the previous study about a model of social networks. Method : The survey was done from January to February in 2001. Total 257 mothers who have four to twelve month old first-time baby was interviewed in five community health center around country(Seoul, Choung-ju, Asan, Cheon-an, Jeju). Finally 247 data was analyzed. Data analysis was done with LISREL 8.20 program for covariance structural analysis. Results : Compared to the hypothetical model, the revised model has become parsimonious and had a better fit to the data ($X^2=167.55$ (p값=.00), $x^2/df=1.48$, GFI=0.97, AGFI=0.95, RMR=0.049, NFI=0.98, NNFI=0.99, CN=222.53). All predictive variables of the maternal role of first-time mother explained 30% of total variance in model. Social network structural characteristics and social network interactional characteristics had significant effect on the emotional support and the information support. And social network interactional characteristics had significant effect on the service support, material support and social companionship support. The service support and social companion ship support had significant effect on the maternal role strain. The emotional support and the social companion ship support had significant effect on the maternal role of first-time mother. Conclusion : As the conclusion of this study, there is in need of the developing the programmes focussed on the social network for the first-time mother.

• 한국유통학회지:유통연구
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• 제16권2호
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• pp.95-118
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• 2011

본 연구는 다음과 같은 연구목적을 가진다. 첫째, 프랜차이즈 시스템에서 사회연결망 밀도와 중앙성이 가맹점의 가맹본부와의 정보공유와 다른 가맹점들과의 정보공유에 미치는 영향에 대한 관계를 실증적으로 밝히고자 한다. 둘째, 앞서 제시한 관계들에 있어 가맹점과 가맹본부 간의 유대강도의 조절역할을 하는지에 대하여 탐색적으로 확인하고자 한다. 셋째, 실증분석의 결과를 토대로 학문적 실무적 시사점을 제시하고자 한다. 본 연구는 실증분석을 하기 위하여 부산지역에 소재한 프랜차이즈 가맹점들을 대상으로 설문조사를 실시하였으며, 설문응답의 신뢰성을 높이기 위해서 가맹점의 점주와 점장을 중심으로 설문조사 하였다. 회수된 설문지는 총 200부이며, 이 중 무성의하게 응답한 11부를 제외한 189부를 실증분석에 사용하였다. 평균변환법과 위계적 다중회귀분석법을 사용하여 가설들을 검증한 결과는 다음과 같다. 첫째, 정보공유 대상이 가맹본부인 경우 사회연결망 중앙성, 유대강도, 밀도 및 중앙성과 유대강도의 상호작용이 정보공유에 유의하게 영향을 미치는 것으로 나타났다. 둘째, 정보공유 대상이 다른 가맹점인 경우 사회연결망 중앙성이 정보공유에 유의한 영향을 미치는 것으로 나타났다. 마지막으로 본 연구의 실증분석 결과를 토대로 학문적 실무적 시사점과 본 연구의 한계점 및 향후 과제를 제시하였다.

• Journal of Information Processing Systems
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• 제10권2호
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• pp.271-282
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• 2014

The advancement of knowledge society has enabled the social network community (SNC) to be perceived as another space for learning where individuals produce, share, and apply content in self-directed ways. The content generated within social networks provides information of value for the participants in real time. Thus, this study proposes the social network community activity-based content model (SoACo Model), which takes SNC-based activities and embodies them within learning objects. The SoACo Model consists of content objects, aggregation levels, and information models. Content objects are composed of relationship-building elements, including real-time, changeable activities such as making friends, and participation-activity elements such as "Liking" specific content. Aggregation levels apply one of three granularity levels considering the reusability of elements: activity assets, real-time, changeable learning objects, and content. The SoACo Model is meaningful because it transforms SNC-based activities into learning objects for learning and teaching activities and applies to learning management systems since they organize activities -- such as tweets from Twitter -- depending on the teacher's intention.

• 산업경영시스템학회지
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• 제35권3호
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• pp.62-69
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• 2012

This thesis proposes a new social network simulator, which can be used for the social network analysis (SNA). It is composed of three modules; initialization, network evolution, and output generation. For the network evolution module, we suggest a modified JGN (MJGN) based on JGN, the network evolution model developed by Jin, Girvan, and Newman. Arena, one of the most popular simulation tools, was used to model the agent based social network simulator. Lastly, some test results were presented to show the value of the proposed simulator when one performs SNA at the longitudinal point of view.

• Journal of information and communication convergence engineering
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• 제21권1호
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• pp.9-16
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• 2023

The natural language on social network platforms has a certain front-to-back dependency in structure, and the direct conversion of Chinese text into a vector makes the dimensionality very high, thereby resulting in the low accuracy of existing text classification methods. To this end, this study establishes a deep learning model that combines a big data ultra-deep convolutional neural network (UDCNN) and long short-term memory network (LSTM). The deep structure of UDCNN is used to extract the features of text vector classification. The LSTM stores historical information to extract the context dependency of long texts, and word embedding is introduced to convert the text into low-dimensional vectors. Experiments are conducted on the social network platforms Sogou corpus and the University HowNet Chinese corpus. The research results show that compared with CNN + rand, LSTM, and other models, the neural network deep learning hybrid model can effectively improve the accuracy of text classification.

• 스마트미디어저널
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• 제3권1호
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• pp.9-15
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• 2014

오늘날 온라인 소셜 네트워크 서비스가 대중화 되면서, 메시지 전송 연구에 있어 소셜 네트워크에 대한 역할을 이해하는 것은 중요한 문제가 되었다. 기존의 온라인 소셜 네트워크상의 메시지 전송에 대한 연구들은 주로 메시지의 확산 범위와 이를 최대화할 수 있는 방법에 대해 다루었다. 하지만 기존의 연구들에서는 구별된 전송 특성을 가지는 다양한 채널들과 서로 다른 채널선호도 및 재전송 특성을 가지는 소셜 네트워크 사용자의 분포가 메시지 전송에 미치는 영향에 대해서는 많이 고려하지 못했다. 이 논문에서는 이러한 다중-형태 다중 -채널을 가지는 소셜 네트워크상의 메시지 전송 프로세스를 모델링하기 위해 Delay Weighted Independent Cascade 모델을 제안한다. 이 모델에서는 소셜 네트워크상의 다양한 채널들(온라인 소셜 네트워크, 이메일, SMS, 전화, 구두전달)을 고려하고 각 채널들은 서로 다른 메시지 전송 시간을 가질 수 있음을 고려하였다. 그리고, 소셜 네트워크의 각 사용자의 특성을 고려하기 위해 사용자 타입에 따라 메시지 재전송 확률 및 채널 선호도를 서로 다르게 설정하였다. 또한, 사용자의 지역 분포를 고려함으로써 다양한 상황에서의 메시지 전송 특성을 분석할 수 있도록 하였다. 제안된 모델을 기반으로 작성된 시뮬레이터를 통해, 다양한 상황의 소셜 네트워크 메시지 전송에 대해 분석하였다.

• 한국정보시스템학회지:정보시스템연구
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• 제18권3호
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• pp.47-70
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• 2009

Social network is one of the representative analytical method of the complexity theory and this research analyzed various and unique strategic alliance model of e-business domain using social network technique. A lot of small and medium firms of e-business field had developed many useful type of strategic alliances for the firms tried to maximize the effect of advertisement, marketing and to make up for their weak points and to compete with huge company with capital strength long before. But it is too rare to analyze the structure of the firm networks and to study the evolution and extension of business model considered the role of each company in the network. Social network analysis helps each firm's network easily visualized and completely modelized. Additionally, this paper cries to analyze the relationship between the role of hub and broke in the firm networks for strategic alliance, and financial performance. We demonstrate the firm with finer business model to the business environment can make higher financial performance. This implies that the firm that can create new finer business model, will lead the network of e-business firms and evolve the industry of e-business.

• 유통과학연구
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• 제15권6호
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• pp.13-24
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• 2017

Purpose - The current study aims to examine the effect of social network factors on travel agency employees' occupational outcomes such as job performance and job satisfaction through innovation behavior in a comprehensive model. Research design, data, and methodology - Based on a theory of social network, the concept of social network was assessed by three factors: a) network size, b) network range, and c) tie strength. To test the proposed hypotheses, structural equation modeling (SEM) was employed based on data from 197 travel agency employees in Korea. Result - The results showed that the associational activity of network size had a positive effect on innovation behavior, while the network range of network size had a significant negative effect on innovation behavior. Subsequently, innovation behavior positively influenced on job performance and job satisfaction, respectively. Conclusions - The results offer some insights into the extended model and have important managerial implications for Korean travel agencies. More specifically, considering diverse domains of social network and organizational research, this study advances critical utility of social network factors in a high facilitating level of innovation behavior, which can help travel agency employees promote their job performance and job satisfaction.