• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1570-1594
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• 2017

Social network services have recently changed from environments for simply building connections among users to open platforms for generating and sharing various forms of information. Existing user reputation computation methods are inadequate for determining the trust in users on social media where explicit ratings are rare, because they determine the trust in users based on user profile, explicit relations, and explicit ratings. To solve this limitation of previous research, we propose a user reputation computation method suitable for the social media environment by incorporating implicit as well as explicit ratings. Reliable user reputation is estimated by identifying malicious information raters, modifying explicit ratings, and applying them to user reputation scores. The proposed method incorporates implicit ratings into user reputation estimation by differentiating positive and negative implicit ratings. Moreover, the method generates user reputation scores for individual categories to determine a given user's expertise, and incorporates the number of users who participated in rating to determine a given user's influence. This allows reputation scores to be generated also for users who have received no explicit ratings, and, thereby, is more suitable for social media. In addition, based on the user reputation scores, malicious information providers can be identified.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.83-90
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• 2010

We describe a novel method for improving the performance of the UCC retrieval using content reputation and user reputation. The UCC retrieval is a part of the information retrieval. The goal of the information retrieval system finds documents what users want, so the goal of the UCC retrieval system tries to find UCCs themselves instead of documents. Unlike the document, the UCC has not enough textual information. Therefore, we try to use the content reputation and the user reputation based on non-textual information to gain improved retrieval performance. We evaluate content reputation using the information of the UCC itself and social activities between users related with UCCs. We evaluate user reputation using individual social activities between users or users and UCCs. We build a network with users and UCCs from social activities, and then we can get the user reputation from the network by graph algorithms. We collect the information of users and UCCs from YouTube and implement two systems using content reputation and user reputation. And then we compare two systems. From the experiment results, we can see that the system using content reputation outperforms than the system using user reputation. This result is expected to use the UCC retrieval in the feature.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2007.02a
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• pp.190-196
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• 2007

With the rapid development of electronic commerce, online reputation management systems are of increasing importance in building trust and managing risk. Reputation rating mode and aggregating method are the most crucial parts of a reputation management system. In this paper, we analyze the merits and disadvantages associated with the rating mode and aggregating approach of current reputation management systems, and put forward some suggestions. These suggestions are helpful in improving current reputation management systems and developing new reputation management systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.847-848
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• 2007

In this work, we analyze the role of reputation in ubiquitous healthcare system as well as the relationship of security, trust and reputation in this environment in details. In addition, an example is given to show how to use reputation system in ubiquitous healthcare and how to use reputation system on decision making.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.139-152
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• 2013

Although a series of studies shows the fact that a company's reputation could affect its sales rate and stock price, due to the increased use of SNS, the research related to the online measurement method for the corporate reputation has been relatively insufficient. This study explores a design for a method to quantify the corporate reputation value by reconstructing the discussions in literature review. Concretely, this study divides the corporate reputation value into the corporate identity information and the corporate awareness information, which includes the following five sub-categories: (1) the quality of product and service; (2) the employment environment; (3) the corporate vision; (4) the social responsibility; and (5) the business achievement. Additionally, for the corporate identity assessment, this study considers the following six factors: (1) Agreeableness (Goodness), (2)Capability (Ability), (3)Enterprise (Rise), (4)Chic (Class), (5) Ruthlessness (Authority), and (6)Informality. Based on these categories and factors, this study develops a technique quantifying the corporate reputation value by selecting 'word items' for the reputation search, and after conducting a frequency analysis in a survey. Also, to verify the result, this study exemplifies the reputation of three SI companies in Korea which could be utilized by using the commercialized reputation service. This study firstly attempts the corporate reputation measurement by classifying the identity and the awareness (corporate image and communication) upon a company in detail and enables its real applicabilities by proposing a formula to measure the reputation scores which can be utilized by verified word items from a frequency analysis.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.2
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• pp.35-47
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• 2004

Though P2P network systems are widely used, not so much research has been done on security issues. One of the serious problem in P2P network is the authentication problem. To resolve this problem, we introduce a new concept, a "self-reputation system" in which a user manages her own reputation. We define self-reputation systems by presenting several requirements. We also give one instance of self-reputation system. The proposed instance satisfies the requirement including the prevention of erasing and the platform independence.ependence.

• Korean journal of communication and information
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• v.60
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• pp.75-103
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• 2012

The purpose of this study is to explore the meaning and the effect of communication as social capital, which needs to be evaluated empirically focusing on corporate reputation. Also, it tried to analyze consumers' communication network in the structural, substantial, and relational level, which is to verify how characteristics and meanings of communication network structure affect to a good corporate reputation. A survey toward 200 participants was conducted during 5 days from March 29 to April 3, 2012. Characteristics of communication network structure of a corporation with higher reputation is analyzed using the index such as degree, degree centrality, and density. The findings of the study show that a corporation with higher reputation has higher network degree, degree centrality, and density compared to a corporation with lower reputation. Consumers of a corporation with higher reputation get information from various overlapping sources. It allows them to share similar interpretation, which could elevate the degree, degree centrality, and density of network. It also proved that when the network density is high, a corporation with higher reputation can distribute information much faster and easier. Moreover, in the substantial level of social capital, product/service information network has high degree and density rather than corporate issue information network. Likewise, degree and density of information acquisition network was higher than those of information provision network. Also, this study verified the effect and relationship between the network structure characteristics and corporate loyalty in a relational level. In this way, the positive effect of the degree centrality on corporate loyalty was supported. In conclusion, as consumers share more information from overlapping sources, the degree of communication network gets higher. Throughout this network, the diffusion of information among consumers would be activated, and this confirmed that corporate reputation and corporate loyalty is closely related.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3793-3814
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• 2021

Most secure solutions like cryptography are software based and they are designed to mainly deal with the outside attacks for traditional networks, but such soft security is hard to be implemented in wireless sensor networks to counter the inside attacks from internal malicious nodes. To address this issue, reputation has been introduced to tackle the inside malicious nodes. Reputation is essentially a stimulating mechanism for nodes' cooperation and is employed to detect node misbehaviors and improve the trust-worthiness between individual nodes. Among the reputation models, binomial distribution based reputation has many advantages such as light weight and ease of implementation in resource-constraint sensor nodes, and accordingly researchers have proposed many insightful related methods. However, some of them either directly use the modelling results, apply the models through simple modifications, or only use the required components while ignoring the others as an integral part of the whole model, this topic still lacks a comprehensive and systematical review. Thus the motivation of this study is to provide a thorough survey concerning each detailed functional components of binomial distribution based reputation for wireless sensor networks. In addition, based on the survey results, we also argue some open research problems and suggest the directions that are worth future efforts. We believe that this study is helpful to better understanding the reputation modeling mechanism and its components for wireless sensor networks, and can further attract more related future studies.

• Journal of KIISE
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• v.42 no.10
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• pp.1286-1293
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• 2015

Most e-marketplaces build a reputation system that provides potential buyers with reputation scores of sellers in order for buyers to identify the sellers that are more reliable and trustworthy. The reputation scores are computed based on the aggregation of buyers' ratings. However, when these ratings are used to compute the reputation scores, the existing reputation systems do not make a distinction according to the following two criteria: the capability of the seller and the quality of an item. We claim that a reputation system needs to separate the two criteria in order to provide more precise information about the seller. In this paper, we propose a method to compute seller's reputation by separating the rating into the seller's score and the item's score. The proposed method computes the reputation of the seller's capability by using only the 'seller's score' and helps potential buyers to find reliable sellers who provide fast delivery and better service. In experiments, we propose a simulation strategy that reflects the real life of an E-marketplace and verify the effectiveness of our method by using the generated simulation data.

• 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.