• Journal of Information Technology Services
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• v.15 no.3
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• pp.127-145
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• 2016

This paper aims to investigate empirically how brand trust can be formed from the customer-brand relationship through a direct use of firm's SNS in B2B context. The brand trust is fundamental elements to understanding of long-term relationship in a B2B context. To achieve the objectives of this study, data collection is through a personally administered questionnaire, and a total of 180 questionnaires was collected from the buyer or supplier who frequently visited partner's firm SNS. Excluding missing data, 120 usable data were analyzed. From the results, first, three SNS motivations (i.e. Information, social and entertainment) has a positive impact on the perceived value of SNS (i.e. perceived usefulness and perceived enjoyment). Second, the perceived usefulness and perceived enjoyment positively affect customer-brand relationship (brand intimacy, brand attachment). Third, the customer-brand relationship is positively related to brand trust. Implications, limitations and future research directions of the study were also discussed. These findings help managers in developing and implementing the relation between SNS use and a customer-brand relationship for long-term relationship in B2B.

• Journal of Broadcast Engineering
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• v.12 no.5
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• pp.452-459
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• 2007

The Internet is encountering a new turning point owing to the raising Web 2.0. A user Just receives the information and service provided by a service provider in the existing web 2.0, but a user can create a new service for himself using an application program and data provided in web 2.0. The digital content market is producing a new service according to Web 2.0. The specific service among them is User Created Contents(UCC) and it is leading to the participation and interesting of user SecondLife also which is the type as Social Network Service(SNS) and VR, is placing as a new service type. This paper defines Web 2.0 environment and classifies as UCC, SNS and Virtual Reality(VR) and defines a variety services shown in new environment. It also analyzes shortcomings and then prospect a new type of service which will be shown in the future.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.61-71
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• 2014

Social networking services have changed the way people communicate. Rapid growth of information generated by social networking services requires effective search methods to give useful results. Over the last decade, social search methods have rapidly evolved. Traditional techniques become unqualified because they ignore social relation data. Existing social recommendation approaches consider social network structure, but social context has not been fully considered. Especially, the friend recommendation is an important feature of SNSs. People tend to trust the opinions of friends they know rather than the opinions of strangers. In this paper, we propose a levelized data processing method for social search in ubiquitous environment. We study previous researches about social search methods in ubiquitous environment. Our method is a new paradigm of levelelized data processing method which can utilize information in social networks, using location and friendship weight. Several experiments are performed and the results verify that the proposed method's performance is better than other existing method.

• The Journal of Bigdata
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• v.2 no.1
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• pp.27-39
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• 2017

The importance of online communication is getting increased by the rapid growth of smartphone supply and Social Network Service (SNS) use. Catching up with the trend, firms are actively use SNS to improve brand image, promote products, and communicate with customer. On the one hand, SNS is the channel for firms' marketing activities, but on the other, it is also the channel where the events related to the firms propagate in real time. Firms are led to unexpected state of crisis, when events are quickly spread out on SNS. Then firms are assessed their image by the way they deal with the state of crisis. This paper proposes to figure out user response on SNS according to each crisis response strategies by analyzing event-related twitter data when crisis situations of firms arise. We classify crisis response strategies into response attitude, defensive and accommodative response, and response speed, fast and slow response. This paper suggests optimal crisis response strategy to firms regarding state of crisis propagated on SNS.

• Knowledge Management Research
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• v.19 no.1
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• pp.19-39
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• 2018

With the development of information technology, social network services (SNS) such as Facebook and Twitter became popular and many users disclose their personal and sensitive information like private story, photographs and location information through posting and sharing. Despite the privacy concerns in SNSs, individuals continue to disclose their identity online. This phenomenon is called 'privacy paradox'. The purpose of this study is to examine the role of collective efficacy on self-disclosure in SNS context and to explain privacy paradox phenomenon. Drawing upon the communication privacy management theory, research model was developed and empirically tested with cross-sectional data from 306 individuals. Results revealed that collective efficacy has a direct positive effect on self-disclosure while privacy risk is negatively related to self-disclosure. However, privacy concern is not directly related to self-disclosure. The relationship between privacy concern and self-disclosure was moderated by collective efficacy.

• Information Systems Review
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• v.20 no.2
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• pp.63-85
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• 2018

Emerging hotspot and trendy areas are formed into alleys and blocks with the help of viral effects among social network services (SNS) users called "Golmogleo." These users search for every corner of the alleys to share and promote their own favorite places through SNS. An analysis of hot places is limited if it is only based on macroeconomic indicators such as commercial area data published by national organizations, large-scale visiting facilities, and commuter figures. Careful analyses based on consumers' actual activities are needed. This study develops a "social big data analysis methodology" using Instagram data, which is one of the most popular SNSs suitable to identify recent consumer trends. We build a spatial analysis model using Local Moran's I. Results show that our model identifies new trend zones on the basis of posting data in Instagram, which are not included in the commercial information prepared by national organizations. The proposed analysis methodology enables better identification of the latest trend areas formulated by SNS user activities. It also provides practical information for start-ups, small business owners, and alley merchants for marketing purposes. This analytical methodology can be applied to future studies on social big data analysis.

• Journal of Service Research and Studies
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• v.14 no.3
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• pp.60-78
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• 2024

Social Network Service(SNS) has fundamentally changed the scope, boundaries, and dynamics of social interactions, becoming an integral part of everyday social communication for individuals and significantly altering the decision-making processes of individuals and organizations. Although prior studies have agreed that individual motivations significantly affect travel experience sharing behavior on SNS, different motivations need to be further examined. Also, there is little empirical study that examines the relationships between social capital and motivations. To address these gaps, this study developed a research model to investigate how two types of social capital (i.e., bridging and bonding) influence individual motivations (i.e., self-enhancement and altruism motivations), which in turn contributes to travel experience sharing behavior on SNS. The online survey was conducted from March 3 to March 17, 2021, and 516 responses were included in the data analysis. Structural Equation Modeling was applied to test the hypotheses in a research model. This research provided a comprehensive exploration of the relationship between motivations and social capital, contributing to a better understanding of why tourists share their travel experiences on SNS.

• Journal of Information Technology Applications and Management
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• v.19 no.1
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• pp.25-36
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• 2012

Social Commerce recently attracted the attention of academic and industry researchers. Social Commerce aims to make a transactional environment which is beneficial to three parties-social commerce service provider, buyer and seller by way of using the platform of SNS. As Social Commerce is a new technology issue, there is no existing conceptual framework, e.g. appropriate classification the business types, that help to understand the nature of Social Commerce. This study suggests one classification framework and tries to verify whether it works.

• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.5
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• pp.858-871
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• 2017

The present study purported to understand the relationships between SNS appearance-related photo activity, body image and self-esteem among young women. Objectification Theory and Social Comparison Theory explain the process how young women's SNS appearance-related photo activity influence their body satisfaction through a perceived media pressure, objectification of their own bodies and appearance comparison. These process ultimately affect the self-esteem of young female users. A research model was proposed and related hypothesis were examined. We collected an online questionnaire from 400 female participants in their 20's. Data were analyzed using SPSS 23.0 and AMOS 18.0. Structural equation modeling analyses suggested that the proposed research model provided a good fit to the data and supported most hypothesis. The results indicated that the level of SNS appearance-related photo activity significantly influences young female user's body satisfaction and self-esteem. The findings of this study were consistent with previous literature on media and body image. Limitations and future research suggestions were also described.

• Korea Journal of Hospital Management
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• v.23 no.4
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• pp.26-39
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• 2018

Purposes: The purpose of this study is to analyze the issue of interest in patient medical service of small and medium hospitals using big data. Methods: The method of this study was implemented by data mining and social network using SNS big data. The analysis tool were extracted key keywords and analyzed correlation by using Textom, Ucinet6 and NetDraw program. Findings: In the results of frequency, the network-centered and closeness centrality analysis, It was shown that the government center is interested in the major explanations and evaluations of the technology, information, security, safety, cost and problems of small and medium hospitals, coping with infections, and actual involvement in bank settlement. And, were extracted care for disabilities such as pediatrics, dentistry, obstetrics and gynecology, dementia, nursing, the elderly, and rehabilitation. Practical Implications: Future studies will be more useful if analyzed the needs of customers for medical services in the metropolitan area and provinces may be different in the small and medium hospitals to be studied, further classification studies.