• The Journal of Society for e-Business Studies
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• v.18 no.1
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• pp.33-55
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• 2013

Information sharing behavior in the Internet has raised much interest. Recently, social network sites provide a new information sharing channel for the users who want to connect with others based on common social background or tastes. Especially, we focus that a social network site becomes one of major routes for information sharing about socially influential issues. Therefore, studying how information is diffused via a social network site may give theoretically, practically significant implication. Based on the assertion, we investigated user's behavior to mediate other user's information messages. We define information mediating behavior as concurrent actions of filtering and distributing behavior of the digital content that is originated from one of the connected users. In this study, we intended to understand the effects of information mediating behavior, and tried to understand characteristics of re-mediating of previously mediated information. Using an agent-based simulation model, we found that information mediating behavior increased the extent of information diffusion significantly. In addition, even a small degree of mediating probability could boost up the level of information diffusion in the case of a re-mediating condition. We believe that those findings provide remarkable insight of research and business application on both of information sharing and diffusion in a social network site.

• Journal of Service Research and Studies
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• v.1 no.1
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• pp.49-60
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• 2011

Recently, with the growing of social network sites, people's choice is also getting more and more. So the notion of loyalty has become an important construct within the Social Network framework because of member is easy switching on the social networking sites. Despite the increasing importance of social network sites loyalty question, there's very little research in this area. In electronic commerce, the website loyalty development process is based on both website satisfaction and website trust toward the net-enabled business. But how to target the members with high or low loyalty in the social network sites is still a question. In this paper we propose one improved RFM model to evaluate the member loyalty to find the potential members for improving the service quality of the social network site. In addition, an empirical case study is performed to demonstrate how this procedure works. Moreover, further applications of this research are provided for improved social network sites experiences and how to use the model to practice.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.224-236
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• 2023

This study aims to investigate the effects of telepresence on young moviegoers' flow experiences and social interactions, and the impact on consumer delight, trust, and experience sharing behavior on cinema mobile social network site pages. Given the scarcity of telepresence research, indirect telepresence on experience sharing via two experiences and social interactions is also included. The study used pages from Korean cinema mobile social network sites, and 175 Chinese moviegoers residing in Korea participated. We found that telepresence positively impacts the activity in both human-human and human-computer interactions. We further contend that telepresence positively affects perceived enjoyment and attentional focus. However, perceived enjoyment does not significantly affect consumer delight. We found that consumer delight positively influences consumer trust and movie experience sharing. Moreover, we illustrated that telepresence significantly and indirectly influences consumer movie experience-sharing behavior through attention focus and consumer delight. Our results provide crucial insights for future study and practical managerial.

• The Research Journal of the Costume Culture
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• v.23 no.3
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• pp.498-511
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• 2015

This paper examines advertising images of fashion brands in vertical social network site (SNS) from the viewpoints of message strategies. Vertical social network sites are types of social curation systems applied to social networking, where information is selected, organized, and maintained. Fashion brands communicate with consumers by presenting images on vertical SNSs, anticipating improvements in brand image, popularity, and loyalty. Those images portray content for particular brands and seasonal concepts, thus creating paths for product sales information. Marketing via SNSs corresponds to relationship marketing, which refers to long-term interrelationship and value augmentation between the company and consumer, and viral advertising, which relies on word of mouth distribution via social network platforms. Taylor's six-segment message strategy wheel, often used for analyzing viral ads, was applied to conduct a content analysis of the images. A total of 2,656 images of fashion brands advertised on Instagram were selected and analyzed. Results indicated that brand values were somewhat related to the number of followers. Follower rankings and comment rankings were also correlated. In general, fashion brands projected sensory messages most often. Acute need and rational messages were less common than other messages. Sports brands and luxury brands presented sensory messages, whereas fast fashion brands projected routine images most often. Fashion brands promoted on vertical SNSs should portray advertising images that combine message strategies

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.113-119
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• 2020

Numerous tourist-related data produced on the Internet contain not only simple tourist information but also diverse ideas and opinions from users. In order to derive meaningful information about tourist sites from such big data, the social network analysis of tourist keywords can identify the frequency of keywords and the relationship between keywords. Thus, it is possible to make recommendations more suitable for users by utilizing the clear recommendation criteria of tourist attractions and the relationship between tourist attractions. In this paper, a recommendation system was designed based on tourist site information through big data social network analysis. Based on user personality information, the types of tourism suitable for users are classified through deep learning and the network analysis among tourist keywords is conducted to identify the relationship between tourist attractions belonging to the type of tourism. Tour information for related tourist attractions shown on SNS and blogs will be recommended through tagging.

• The Journal of Information Systems
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• v.24 no.1
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• pp.67-94
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• 2015

Recently, the popularity of Social Network Service (SNS) along with the spread of smart phone, personal computer and tablet PC helps personal network to construct new forms of services in cyberspace. As such, SNS plays a significant role in constructing diverse online networks and there is a growing interest on SNS at societal level. In this vein, the purpose of the research was to find the factors affecting the continuance intention to use social network services. The major findings are summarized as follows. First, "System Quality", "Contents Quality", "Personal Innovativeness", "Self-Efficiency", "Honor Benefit" has significant effects on "Relationship Quality". Yet, "Economic Benefit" is not statistically significant on "Relationship Quality". Second, "Relationship Quality" has a significant effect on "Continuous Usage Intention". Last, our research discovered the relationship between exogenous variables which would serve as valuable inputs in the development of strategic guideline and plan for SNS companies and related services.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1169-1179
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• 2011

Through social network analysis using portal site information, we study the relation of the probability distributions that appear in statistics textbooks with probability distributions that appear in daily life. Based on daily life, we discuss probability distributions that must be emphasized in frequent use.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.4
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• pp.395-402
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• 2017

Social network service provides an excellent platform for people seeking for advices. This research analyzed the effect of rational and emotional response and social distance on people's acceptance for advices online by the construal level theory. An experiment was completed to test the relationship between advisers and questioners and verify the content of online feedback would influence people's acceptance for advices on social network site. The online response included emotional advice and rational advice. Social distance between advisers and questioners was divided to close social distance condition and distant social distance condition. The study showed: (1) comparing with emotional advice, rational advice had a higher persuasive effect in both close and distant social distance conditions; (2) the impact of feedback from people with close social distance was stronger than the impact of the advices from people with distant social distance; (3) there existed an interaction effect between social distance and affective advice. The results revealed that the adviser's affective expression and relationship with the questioner would interactively impact the online persuasive effect.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.213-226
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• 2013

Recently, the social commerce on Facebook.com and Twitter.com, which is represented by SNS (Social Network Service), has been expanding in the form of a combination of SNS market. This study attempted to examine the cost-effect analysis between portal-based advertisement and SNS-based advertisement in order to establish an effective advertising strategy for e-learning content providers. The results showed that portal-based advertisement is more effective than SNS-based advertisement in terms of advertising effectiveness against cost. According to these empirical research results, this article discusses the practical implications for e-learning content providers in an attempt to enable them to take competitive advantage.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.305-316
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• 2021

The objective is to recognize the better opportunities from targeted reveal advertising, to show a banner ad to the consumer of online who is most expected to obtain a preferred action like signing up for a newsletter or buying a product. Discovering the most excellent commercial impression, it means the chance to exhibit an advertisement to a consumer needs the capability to calculate the probability that the consumer who perceives the advertisement on the users browser will acquire an accomplishment, that is the consumer will convert. On the other hand, conversion possibility assessment is a demanding process since there is tremendous data growth across different information dimensions and the adaptation event occurs infrequently. Retailers and manufacturers extensively employ the retail services from internet as part of a multichannel distribution and promotion strategy. The rate at which web site visitors transfer to consumers is low for online retail, out coming in high customer acquisition expenses. Approximately 96 percent of web site users concluded exclusive of no shopper purchase[1].This category of conversion rate is collected from the advertising of social media sites and pages that dataset must be estimating and assessing with the concept of big data clustering, which is used to group the particular age group of people along with their behavior. This makes to identify the proper consumer of the production which leads to improve the profitability of the concern.