• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.390-394
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• 2009

The semantic web-based social network is highly useful in a variety of areas. In this paper we make diverse analyses of the FOAF-based social network, and propose an expert recommendation system. This system presents useful method of ontology-based social network using SparQL, RDFS inference, and visualization tools. Then we apply it to real social network in order to make various analyses of centrality, small world, scale free, etc. Moreover, our system suggests method for analysis of an expert on specific field. We expect such method to be utilized in multifarious areas - marketing, group administration, knowledge management system, and so on.

• Journal of Advanced Technology Convergence
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• v.1 no.2
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• pp.27-35
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• 2022

We investigated the role of product-influencer congruence between social distance, perceived authenticity and attitude toward ads. In particular, we focused on the mediating effect of perceived authenticity on the relationship between social distance and attitude toward ads. Also, we interested in the conditional indirect effect of product-influencer congruence on the mediation process. For our purposes, data were collected from a convenience sample of 340 undergraduate students at a large university in South Korea. Our results indicated that social distance is directly related to the perceived authenticity and, consequently, affects attitude toward ads. Also, an indirect effect of the perceived authenticity was significant on the low level of product-influencer congruence and not in the high level. Our findings suggest that marketing managers should consider the social media influencer's authenticity and congruence between the product and the influencer.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.125-134
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• 2014

As the social media which was simple communication media is activated on account of twitter and facebook, it's usability and importance are growing recently. Although many companies are making full use of its the capacity of information diffusion for marketing, the adverse effects of this capacity are growing. Because social network is formed and communicates based on friendships and relationships, the spreading speed of the spam and mal-ware is very swift. In this paper, we draw parameters affecting malicious data diffusion in social network environment, and compare and analyze the diffusion capacity of each parameters by propagation experiment with XSS Worm and Koobface Worm. In addition, we discuss the structural characteristics of social network environment and then proposed malicious data propagation model based on parameters affecting information diffusion. n this paper, we made up BA and HK models based on SI model, dynamic model, to conduct the experiments, and as a result of the experiments it was proved that parameters which effect on propagation of XSS Worm and Koobface Worm are clustering coefficient and closeness centrality.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.153-169
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• 2011

Today using Internet environment is considered absolutely essential for establishing corporate marketing strategy. Companies have promoted their products and services through various ways of on-line marketing activities such as providing gifts and points to customers in exchange for participating in events, which is based on customers' membership data. Since companies can use these membership data to enhance their marketing efforts through various data analysis, appropriate website membership management may play an important role in increasing the effectiveness of on-line marketing campaign. Despite the growing interests in proper membership management, however, there have been difficulties in identifying inappropriate members who can weaken on-line marketing effectiveness. In on-line environment, customers tend to not reveal themselves clearly compared to off-line market. Customers who have malicious intent are able to create duplicate IDs by using others' names illegally or faking login information during joining membership. Since the duplicate members are likely to intercept gifts and points that should be sent to appropriate customers who deserve them, this can result in ineffective marketing efforts. Considering that the number of website members and its related marketing costs are significantly increasing, it is necessary for companies to find efficient ways to screen and exclude unfavorable troublemakers who are duplicate members. With this motivation, this study proposes an approach for managing duplicate membership based on the social network analysis and verifies its effectiveness using membership data gathered from real websites. A social network is a social structure made up of actors called nodes, which are tied by one or more specific types of interdependency. Social networks represent the relationship between the nodes and show the direction and strength of the relationship. Various analytical techniques have been proposed based on the social relationships, such as centrality analysis, structural holes analysis, structural equivalents analysis, and so on. Component analysis, one of the social network analysis techniques, deals with the sub-networks that form meaningful information in the group connection. We propose a method for managing duplicate memberships using component analysis. The procedure is as follows. First step is to identify membership attributes that will be used for analyzing relationship patterns among memberships. Membership attributes include ID, telephone number, address, posting time, IP address, and so on. Second step is to compose social matrices based on the identified membership attributes and aggregate the values of each social matrix into a combined social matrix. The combined social matrix represents how strong pairs of nodes are connected together. When a pair of nodes is strongly connected, we expect that those nodes are likely to be duplicate memberships. The combined social matrix is transformed into a binary matrix with '0' or '1' of cell values using a relationship criterion that determines whether the membership is duplicate or not. Third step is to conduct a component analysis for the combined social matrix in order to identify component nodes and isolated nodes. Fourth, identify the number of real memberships and calculate the reliability of website membership based on the component analysis results. The proposed procedure was applied to three real websites operated by a pharmaceutical company. The empirical results showed that the proposed method was superior to the traditional database approach using simple address comparison. In conclusion, this study is expected to shed some light on how social network analysis can enhance a reliable on-line marketing performance by efficiently and effectively identifying duplicate memberships of websites.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.147-159
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• 2022

Nowadays, various social media platforms are widely spread and people closely use such platforms in daily life. By doing so, social influencers with a large number of subscribers, views, and comments have huge impact in our society. Following this trend, many companies are actively using influencers for marketing purpose to promote their products and services. In this study, we extract the speeches of influencers from videos for game marketing and analyze them using various text mining techniques. In the analysis, we distinguish game videos leading to successful marketing and failed marketing, and we explore and compare the linguistic features of the influencers for successful and failed marketings.

• Knowledge Management Research
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• v.22 no.4
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• pp.135-155
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• 2021

With the emergence of various types of social media and the diversification of their roles, it has become essential for marketers to understand how different types of social media influence consumers' purchase decisions differently and derive more detailed strategies by social media types. This study classifies social media into two types-expression-focused social media and relationship-focused social media-and investigates the relationship between consumer purchases and social media mentions by type. Using the Seoul bike-sharing data and time-series data for social media mentions, we apply the VAR model with Exogenous Variables (VARX). We find that the increase of product mentions in expression-focused social media positively affects both the number of new customers (customer acquisition) and the number of shared bike rentals, while that in relationship-focused social media negatively affects the number of new customers only. In addition, as new customers increase, the product mentions in both types of social media increase. On the other hand, the number of bike rentals has no significant effect in increasing social media mentions regardless of type. This study contributes to the social media and sharing economy literature and provides managerial implications for establishing sophisticated social media marketing in bike-sharing businesses.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.135-142
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• 2015

Appearance and rapid growth of the social network services (SNS) have led to changes in the distribution structure of information. Consumers can obtain various information quickly via the social network services and companies make use of a new advertising channel in them. In order to increase the effect of publicity activities through the social network services, development and application of public relations strategy by evaluating and analyzing the results of the activities is required. In this paper, a method for developing a low cost system to evaluate and analyze the results of public relations through the social networks is proposed. The proposed method was verified through building and running a demo system to collect and analyze data in the Facebook fan pages using MySQL database and PHP script on a Linux server.

• The Journal of the Korea Contents Association
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• v.17 no.4
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• pp.108-118
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• 2017

This study focuses on an effectiveness of socially recommended advertising on social network sites (SNSs) and investigates the impact of three critical factors on SNS advertising effectiveness - reward type for advertising recommenders' intention, product type on advertisements, and tie strength. A $2{\times}2$ factorial design was used to test the interaction effects between the two variables, reward type and product type on advertisements, moderated by tie strength. The results indicate that when participants observe socially recommended advertising, hedonic product ads with non-monetary reward shows the most effectiveness, and reward type and product type are also effective. In the combination of reward type and product type, we have confirmed the regulating factor influencing the effectiveness of social advertising according to the tie strength between the recommenders and the consumers. Strong-tie recommenders have more influence on the effectiveness of the social advertising than weak-tie recommenders. Based on these results, theoretical and practical implications were provided to refine marketing environments on SNSs.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.311-321
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• 2012

This study derived from 5 variables(information, product diversity, communication possibility, responsiveness, price) of service quality on social commerce from literature studies and set up the research model and hypotheses. The 167 questionnaires are used in this analysis. The results were as follows: first, all the variables had positive influences upon satisfaction except responsiveness. Second, all the variables had positive influences upon repurchase intention except price. Third, the satisfaction of social commerce had a positive influence upon repurchase intention. This study suggested the strategic implications to induce customers satisfaction and repurchase intention after analyzing critical factors about service quality of social commerce.

• Journal of Korean Library and Information Science Society
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• v.48 no.4
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• pp.181-207
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• 2017

The purpose of this paper is to provide values and effectiveness to libraries making a new social network service marketing model and strategy. According to study, when libraries entice library users with social network services, the users become loyal customers who give libraries long-term supports. For method of study, it establishes 15 hypotheses and proves those hypotheses with 157 responders. After inspecting hypotheses, 13 hypotheses are adopted and 3 hypotheses are dismissed. During the research, it is verified that usefulness perceived by library users is the most important factor of user satisfaction and continuous use intention which increased library users' intention to continue visiting the library. In addition, effectivness of marketing and cause are found in order of system quality, information quality, reliability, interactivity, subjective norms. In other words, the study found that library users found their information for using social network services and this attribute affects user satisfaction and ultimately continuous use intention in a positive way.