CommTrust: Computing Multi-Dimensional Trust by Mining E-Commerce Feedback Comments

Zhang, Xiuzhen; Cui, Lishan; Wang, Yan

doi:10.1109/tkde.2013.177

Cited by 60 publications

(34 citation statements)

References 36 publications

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“…The work in [24] presented a framework for building distributed, dependable reputation management systems, with counter measures against vulnerabilities. In [9], the authors defined a reputation evaluation method based on reputation value and reputation prediction variance value based on the aggregation of feedback. In [25], the authors introduced an adaptive and dynamic reputation-based trust model to evaluate trustworthiness, based on community feedback about participants' past behavior.…”

Section: Trust-related Research In Pervasive Networkmentioning

confidence: 99%

“…According to the difference of mathematical tools used in the trust computation, the concrete methods can be based on deterministic mathematics theory, probability theories, and uncertainty theories [6,9,11]. The trust computation models mainly involve the expression of measurement of the concept of trust, a description of the relationship between reputation and trust, and a calculation of trust, which will be discussed thoroughly.…”

Section: Trust Research Approaches In E-commercementioning

confidence: 99%

“…Different methods of qualitative analysis and computational models of trust are proposed gradually [4][5][6][7]. In the application of e-commerce, the degree of trust is obtained by the method of evaluation or rating; calculation methods are simple such as average or summary [6,8,9]. In recent years, the evaluation methods of trust based on the theories of mathematics have attracted attention [4,[10][11][12].…”

Section: Introductionmentioning

confidence: 99%

“…Unfortunately, recently proposed computation approaches of trust and reputation are mainly focused on peer-to-peer networks, ad hoc networks, sensor networks, semantic Web, autonomic computing, grid computing, and multi-agent systems in pervasive computing environments [10,[15][16][17]. In addition, a trust mining method through feedback comments for e-commerce was proposed last year [9]. Our previous work on trust and reputation has mainly investigated the factors of trust in BtoC e-commerce [18], proposed a recommended trust evaluation method for BtoC e-commerce based on the fuzzy analytic hierarchy process [19], and established a reputation evaluation computation model based on the relationship of trust and reputation [20].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Closed-Loop Feedback Computation Model of Dynamical Reputation Based on the Local Trust Evaluation in Business-to-Consumer E-Commerce

Tian

Han²,

Liu³

2016

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Trust and reputation are important factors that influence the success of both traditional transactions in physical social networks and modern e-commerce in virtual Internet environments. It is difficult to define the concept of trust and quantify it because trust has both subjective and objective characteristics at the same time. A well-reported issue with reputation management system in business-to-consumer (BtoC) e-commerce is the "all good reputation" problem. In order to deal with the confusion, a new computational model of reputation is proposed in this paper. The ratings of each customer are set as basic trust score events. In addition, the time series of massive ratings are aggregated to formulate the sellers' local temporal trust scores by Beta distribution. A logical model of trust and reputation is established based on the analysis of the dynamical relationship between trust and reputation. As for single goods with repeat transactions, an iterative mathematical model of trust and reputation is established with a closed-loop feedback mechanism. Numerical experiments on repeated transactions recorded over a period of 24 months are performed. The experimental results show that the proposed method plays guiding roles for both theoretical research into trust and reputation and the practical design of reputation systems in BtoC e-commerce.

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Section: Trust-related Research In Pervasive Networkmentioning

confidence: 99%

Section: Trust Research Approaches In E-commercementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Closed-Loop Feedback Computation Model of Dynamical Reputation Based on the Local Trust Evaluation in Business-to-Consumer E-Commerce

Tian

Han²,

Liu³

2016

Information

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“…Accuracy is measured using precision or recall functions. The CommTrust [2] system consists of a multidimensional trust model for computing reputation scores from user feedback comments. The system is dependent on the idea that users will express themselves freely in textual feedbacks about different aspects of the transactions.…”

Section: Dmentioning

confidence: 99%

Literature Analysis on Reputation Models for Feedback in E-commerce

Thomas¹,

Joseph²

2015

International Journal of Advanced Research in Computer and Comm

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Trust and reputation are decisive factors in internet service provision. The concept is to let the parties rate each other. Reputation models used in e-commerce have the main intention to guide the customers or buyers in a proper way so that they can choose between the different available trustworthy sellers. The models are meant to project the different sellers as per their services and quality. Models are a real need because most of the e-commerce systems have different qualities. But models differ between each other by the methods they opt to calculate the trustworthiness measure for different sellers. Based on such calculations the ranking of the sellers will also vary. Feedback mining method of trust calculation outperforms all other methods with the idea that users are free to express themselves in textual feedback comments. The method addresses the issue of positive bias which has become a major concern nowadays in the field of e-commerce.

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Beyond mean rating: Probabilistic aggregation of star ratings based on helpfulness

Tay

Zhang

Karimi

2019

Asso for Info Science & Tech

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The star-rating mechanism of customer reviews is used universally by the online population to compare and select merchants, movies, products, and services. The consensus opinion from aggregation of star ratings is used as a proxy for item quality. Online reviews are noisy and effective aggregation of star ratings to accurately reflect the "true quality" of products and services is challenging. The mean-rating aggregation model is widely used and other aggregation models are also proposed. These existing aggregation models rely on a large number of reviews to tolerate noise. However, many products rarely have reviews. We propose probabilistic aggregation models for review ratings based on the Dirichlet distribution to combat data sparsity in reviews. We further propose to exploit the "helpfulness" social information and time to filter noisy reviews and effectively aggregate ratings to compute the consensus opinion. Our experiments on an Amazon data set show that our probabilistic aggregation models based on "helpfulness" achieve better performance than the statistical and heuristic baseline approaches.

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CommTrust: Computing Multi-Dimensional Trust by Mining E-Commerce Feedback Comments

Cited by 60 publications

References 36 publications

Closed-Loop Feedback Computation Model of Dynamical Reputation Based on the Local Trust Evaluation in Business-to-Consumer E-Commerce

Closed-Loop Feedback Computation Model of Dynamical Reputation Based on the Local Trust Evaluation in Business-to-Consumer E-Commerce

Literature Analysis on Reputation Models for Feedback in E-commerce

Beyond mean rating: Probabilistic aggregation of star ratings based on helpfulness

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