Reputation systems

By Paul Resnick, Ko Kuwabara, Richard J. Zeckhauser, Eric J. Friedman. CACM, 2000

2,400 citations recorded by the source corpus.

Subfields: Communication, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/67b5617151d8112d0515fee34bd6de467b55ee7b

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In Communication

In Management Science and Operations Research

Citations in the corpus

A survey of trust and reputation systems for online service provision (2007, background): “According to Resnick et al. [56], reputation systems must have the following three properties to operate at all: (1) Entities must be long lived, so that with every interaction there is always an expectation of future interactions.”
Blockchain Governance—A New Way of Organizing Collaborations? (2020, background): “Cus-tomers may rely on online reviews to gain knowledge about the reputation of a given supplier (Resnick et al. 2000).”
Trustworthiness Management in the Social Internet of Things (2014, background): “As described in [15], all information can be stored in a centralized storage to foster sharing and make easy the processing; however, it easily leads to a single point of failure.”
Netprobe: a fast and scalable system for fraud detection in online auction networks (2007, background): “Our experiments prove that Incremental NetProbe executes nearly doubly fast as compared to NetProbe, while retaining over 99% of its accuracy.”
A review of volunteered geographic information quality assessment methods (2017, background): “Resnick et al. (2000) described contributors’ abilities and dispositions as features where this reputation can be based upon.”
A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents (2008, background): “Positive Reputation of Selling Party (REP) has been considered a key factor for reducing risk [4,22,108,125] creating trust [50,59,77] because it provides information that the selling party has honored or met its obligations toward other consumers in the past.”
What makes a useful online review? Implication for travel product websites. (2015, background): “As such, consumers can utilize reputation as an indication of the quality of information to reduce uncertainties regarding information quality (Helm & Mark, 2007; Resnick et al., 2000).”
Secure Multiparty Computations on Bitcoin (2014, neutral): “76 COMMUNICATIONS OF THE ACM | APRIL 2016 | VOL. 59 | NO. 4”
The Effects of Consumer Knowledge on Message Processing of Electronic Word of Mouth via Online Consumer Reviews (2008, background): “The previous studies in the context of online auction sites like eBay mainly deal with the effect of seller reviews [42–45].”
PeerTrust: supporting reputation-based trust for peer-to-peer electronic communities (2004, background): “Reputation systems [28] provide a way for building trust through social control by utilizing communitybased feedback about past experiences of peers to help making recommendation and judgment on quality and reliability of the transactions.”
Controversial Users Demand Local Trust Metrics: An Experimental Study on Epinions.com Community (2005, background): “A considerable amount of research has been carried on recently on these and related topics, such as Reputation Systems (Resnick et al. 2000), Trust Metrics (Golbeck, Hendler, & Parsia 2003; Ziegler & Lausen 2004; Levien 2003; Massa & Avesani 2004; Guha et al.”
Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets (2008, background): “In contrast, reviewers' self-disclosure that is patterned after community norms communicates reviewers' community identification to others, helps to establish the reviewers' reputation (Resnick et al. 2000), and provides an opportunity to obtain identity-verifying responses from fellow members.”
Crossmod: A Cross-Community Learning-based System to Assist Reddit Moderators (2019, background): “In the distributed approach, users up-vote desirable content making it more visible, and down-vote undesirable content, sometimes even reporting content [24, 41, 57, 58].”
The development of initial trust in an online company by new customers (2004, background): “Feed-back information inﬂuences buyer trust and behavior while the expectation of additional future business, and the threat of retaliation from dissatisﬁed buyers, inﬂuence seller behavior [4,68].”