• 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.

• Journal of Information Technology Applications and Management
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• 제23권2호
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• pp.97-112
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• 2016

Many studies have pointed out that trust is the most important component of social capital. Although there have been lots of attempts to measure level of trust between members of community, it is hard to find studies which examine trust from the standpoint of structural aspects. Because of the recent rapid growth of SNS and openness trend on members and their friendship information, it became possible to understand the structure of trust relationships among users in SNS. This study aims to facilitate interpersonal trust by comparing the structure of the trust network among social network users. For this purpose, it proposes a method to explore the structure of trust network and strategies to evolve toward more open structure. In experiments to distinguish structure of trust network with three social network communities, it is discovered that ADVOGATO has characteristics of open and collective network together whereas EPINION and FILMTRUST have collective and open characteristics respectively.

• 가정과삶의질연구
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• 제15권2호
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• pp.45-58
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• 1997

In the traditional rural community social relationships among the people are the routes of resources. But as industrialization goes on rural community has changed. I wonder that rural housewives have yet the traditional social network structure. This stud purposed to analyze the structure of social network resource exchange and perception of community resources. Results were as follows: 1. In the rural housewife's social network structure network range and depth were affected by family income age of the youngest and farming time. Network boundary was affected by near environmental variables such as community resources and community level of living. 2. Community resources was the most influential variable in the resource exchanged 3. Perception of community resources was affected by network depth and was not by the resource exchange.

• 지식경영연구
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• 제12권2호
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• pp.69-80
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• 2011

This paper reports on a structural view of a knowledge network comprised of clubs and organisationsexpressly concerned with cultural activities in a regional Australian city. Social network analysis showed an uneven distribution of power, influence, and prominence in the network. The network structure consisted of two modules of vertices clustered around particular categories of creative arts and these modules were linked most frequently by several organisations acting as communication hubs and boundary spanners. The implications of the findings include 'network weaving' for improving the network structure and developing a systemic approach for exploring the structures of social action that form community-based knowledge networks.

• 디지털산업정보학회논문지
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• 제10권2호
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• pp.157-171
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• 2014

A organization of social enterprises is to achieve various goals such as private interests, the public nature, and social policy. For fulfilling these goals, we have to understand the various success factors. These success factors were shared among peoples. This study explored a position of structure of social network formed by success factors of Social Enterprises with importance. A position within social network defined a number of link connected other nodes. A position is closely associated with to individual's behaviors, opinions and thinking. We used social network analysis with two mode method for explaining feathers of structure of social network formed by success factors shared among peoples. We choose degree centrality for determining a position within social network. Centrality is a key measure in social network analysis. Results is that shared success factors are operation capital(15.15%) totally, and by Buying experience of products of Social Enterprises, Business Compliance(14.39%) and planning(12.88%), and by usage time of smart devices, Business Support(17.05%) and planning(16.10%). and the dominant success factor was not explored.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권12호
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• pp.5927-5942
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• 2017

Many real networks exhibit overlapping community structures. Recent studies have been performed that analyze the impact of overlapping community structure on information propagation, but few of them concerned with individual behaviors. From this point of view, we propose a Markov process model to evaluate the performance of information propagation in social networks with overlapping community structures. In addition, many individual social behaviors are combined in the model. For example, individuals may exhibit selfish behaviors, such as individual and social selfishness, and people may discard the information after they have used it. The accuracy of the model is verified by simulation. Furthermore, the numerical results show that both overlapping community structure of the network and individual behaviors have a significant impact on the outbreak size and propagation speed of the information. Additionally, the overlapping community structure of the social network can reduce the impact of selfishness on information propagation.

• Asia pacific journal of information systems
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• 제29권3호
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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.

• 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.

• 한국콘텐츠학회논문지
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• 제12권6호
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• pp.438-447
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• 2012

이 연구는 프로배구 선수의 사회연결망 구조를 분석하고, 연결망 주요 변수와 자원교환의 관계를 규명하였다. 이 연구에서는 유목적 표집법을 이용하여 2011년 한국 프로배구팀 중 남자 5개팀과 여자 5개 팀의 선수들을 연구대상으로 선정하였으며, 각 140명을 표집하였다. 그러나 최종 분석에 사용된 데이터는 127명이다. 조사방법은 NGQ(Name Generator Question)를 이용한 면접법을 통하여 실시하였으며, 자료처리방법은 NetMiner 3.0을 활용하여 사회연결망 분석을 실시하였다. 결론은 다음과 같다. 첫째, 프로배구 선수의 사회연결망은 멱함수 법칙을 따르는 척도없는 네트워크였다. 즉, 중앙에 놓여 있는 소수의 선수(노드)가 변방이나 주변에 위치한 다른 선수와의 사회적 관계를 끌어 들이는 부익부 빈익빈 형태를 보였다. 둘째, 프로배구 선수의 사회연결망 구조는 자원교환과 유의한 관련성을 지니고 있다. 즉, 내향 활동성이 높을수록 모든 자원교환에서, 외향 활동성이 높을수록 사교적 자원교환에서, 매개중앙성이 높을수록 모든 자원교환에서, 내향 파워가 높을수록 사교적 자원교환에서, 그리고 외향 파워가 높을수록 모든 자원교환에서 유리하였다. 프로배구 선수의 사회연결망에서의 중앙과 변방의 자리매김 위치는 선수들간의 자원교환에서 유리함을 알 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권11호
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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.