• Journal of KIISE
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• v.43 no.1
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• pp.96-105
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• 2016

Recently, social network services have changed by moving towards an open platform where, as well as simply allowing the building of relationships among users, various types of information can be generated and shared. Since existing user reputation management methods evaluate user reliability based on user profiles, explicit relations, and evaluation, they are not suitable for determining user reliability on social media due to few explicit evaluation. In this paper, we analyze social activities on social media and propose a new user reputation management method that considers implicit evaluation as well as explicit evaluation. The proposed method derives positive and negative implicit evaluation from social activities, and generates user reputation information by field in order to consider user expertise. It also considers the number of users that participate in evaluation in order to measure user influence. As a result, it generates the reputation information of users who have no explicit evaluation and creates user reputation information that is more suitable for social media.

• Management & Information Systems Review
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• v.32 no.3
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• pp.173-188
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• 2013

I guess that e-learning buying behaviors have some selection criteria which are interactivity, contents quality, perceived usefulness, and corporate reputation. And I propose that the effects of selection criteria on adaptation intention are moderated by buyer-user status. To accomplish research purpose, I conducted a field survey with a self-administered questionnaire in both user-buyer and analysed the causal relations among the variables by regression analysis. Findings are these. In all of the customer, interactivity, perceived usefulness, and corporate reputation had positive effects on re-attending intention to another e-learning class. In case of users(students), interactivity, contents quality, and perceived usefulness had positive effects, but buyer(parents) showed both perceived usefulness and corporate reputation had positive effects on re-attending intention.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.235-242
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• 2013

Reputation systems aggregate users' feedback after the completion of a transaction and compute the "reputation" of products, services, or providers, which can assist other users in decision-making in the future. With the rapid growth of online e-Learning content providing services, a suitable reputation system for more credible e-Learning content delivery has become important and is essential if educational content providers are to remain competitive. Most existing reputation systems focus on generating ratings only for user reputation; they fail to consider the reputations of products or services(item reputation). However, it is essential for B2C e-Learning services to have a reliable reputation rating mechanism for items since they offer guidance for decision-making by presenting the ranks or ratings of e-Learning content items. To overcome this problem, we propose a novel collaborative filtering based reputation rating method. Collaborative filtering, one of the most successful recommendation methods, can be used to improve a reputation system. In this method, dual information sources are formed with groups of co-oriented users and expert users and to adapt it to the reputation rating mechanism. We have evaluated its performance experimentally by comparing various reputation systems.

• The KIPS Transactions:PartA
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• v.13A no.7 s.104
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• pp.599-606
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• 2006

As the P2P service does not have any administration authorities that are able to manage the behavior of participants and control the malicious users, malicious user can give harm to legitimate users for the benefit of themselves. To perform the secure transaction with new members who did not have past experiences on transaction, service users can differentiate malicious users and legitimate users by referring to the reputation information that provided by users having past experience. However, users can intentionally give false evaluation to other users on Performed transaction. We call these users as 'liar'. In this Paper, we propose a new reputation system for liar reduction to guarantee an accuracy on reputation information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1568-1576
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• 2015

This paper proposes a prediction reputation system for the anti-SPIT solution in real-time VoIP environment. Increased accuracy of the determination as to whether spam or not by deriving a threshold based on SPIT presence in the existing paper. The existing schemes need to get the user's feedback and/or have experienced the time delay and overload as session initiates due to real-time operation. To solve these problems, the proposed scheme predicts the reputation through the statistical analysis based on the period of session initiation of each caller and the call duration of each receiver. As per the second mentioned problem, this scheme performs the prediction before session initiation, therefore, it's proper for real-time VoIP environment.

• The Journal of Society for e-Business Studies
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• v.18 no.2
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• pp.1-26
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• 2013

Estimating levels of user trust is important for maintaining continuous use of e-commerce systems because trust alleviates user concerns about the invisibility of service providers or their reputation. Conventional trust estimation approaches such as policy-and reputationbased reasoning have focused on the experience of e-commerce systems at an early stage. However, only a few trust reasoning methods have considered the mature stage, which is more related to continuance intention. We propose a trust reasoning method dedicated to the mature stage of using e-commerce systems. In particular, a new method of unobtrusively estimating the degree of user intimacy is developed, because intimacy has been highly associated with trust as well as reputation. Our experiments show that the proposed method is valid and can be used in conjunction with reputation-based trust reasoning.

• Knowledge Management Research
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• v.15 no.3
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• pp.209-228
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• 2014

The explosive growth of social commerce engenders a new business model, that is, infomediary. In a social commerce environment, infomediary works as a personal agent who provides information about various web merchants to help consumers select appropriate merchants for their needs. The purpose of this study is to identify the factors influencing consumer attitudes towards infomediaries in social commerce and examine the relationship between intention to provide word of mouth and consumer attitudes. In total, 170 responses were collected from social commerce infomediary users. The results show that competence and integrity significantly influence user attitudes as trust dimensions. Infomediary reputation and two functional factors (information variety and navigation functionality) turn out to be significant antecedents for user attitudes toward infomediary in social commerce. User attitudes in turn significantly influence the intention to provide word of mouth. Future research and practical implications are also discussed.

• Journal of Information Technology Applications and Management
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• v.19 no.4
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• pp.137-152
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• 2012

As social media such as facebook and twitter is widespread, social commerce appears as a new way of e-commerce. Social commerce is a subset of electronic commerce that involves using social media that supports social interaction and user contributions. From the understanding of social commerce and literature review, we deduced the research model that relationship, collectivism, convenience, usefulness, low price, reputation, and rapidness have influence on satisfaction and repurchase intention. As a result of data analysis, relationship, convenience, usefulness, low price, and rapidness had influence on satisfaction and repurchase intention. And collectivism had influence on relationship. But reputation did not have influence on satisfaction. The focus of this study is on the effect of relationship and collectivism on satisfaction and repurchase, because relationship and collectivism is the major feature of social commerce. Succinctly speaking, collectivism affects relationship among users, in turn, relationship affects satisfaction and repurchase intention. This study gives a contribution to business. Business related with social commerce has to make a business strategy for managing relationship and consider collectivism tendency for selecting target customer.

• Journal of Distribution Science
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• v.8 no.2
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• pp.45-51
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• 2010

This purpose of research is to examine in blog characteristics. To realize the purpose of this study, above all it is nessary to analyse the varius blog characteristics. As like blog reputation, blog unification with buyer, blog information value, and blog interactivity. how to blog characteristics influence on credibility and satisfaction as relationship quality in blog. and presenting goods and brand I n blog, How to influence to buyer intention affect related review results of precedent study about blog research, famed design model and set in connected a hypothesis. result of hypothesis verify in blog characteristics, it is supported a hypothesis blog's supplying information value, blog characteristics. supported a hypothesis blog credibility. The factor on the effect of blog satisfaction is revealed blog unification and blog information value, But blog reputation is effect on blog satisfaction negatively. Even if blog reputation became known others and higher reputation. it is not agree with blog satisfaction. the satisfaction of blog's user is associated with blog credibility. introducing satisfaction of goods and service in blog is not influence buyer buying intention, but buyer credibility of blog is influence buyer's buying intention,

• Asia pacific journal of information systems
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• v.30 no.4
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• pp.832-846
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• 2020

Service organizations increasingly adopt data-based intelligent engines called chatbots in support of the interaction between customers and the companies. Two different types of chatbots have been suggested and introduced by companies leading the adoption of this emerging technology: rule-based chatbots and natural language processing-based chatbots. While the differences between these two types of technologies look relatively clear, the organizational and practical impacts of the differences have not been systematically explored. This study performed an experiment to compare the use of the two different types of chatbots used in practice by two comparable organizations. These two types of actual chatbots were used by Korean on-line shopping malls with similar business models (mobile shopping), length of history, size and reputation. The comparison was made based on such dimensions as usability, searchability, reliability and attractiveness. Contraty to conventional expectation that the superiority in technology will produce superior usability, the results show mixed superiority. The discussion on the reasons is presented.