Online reputation mechanisms need honest feedback to function effectively. Self interested agents report the truth only when explicit rewards offset the cost of reporting and the potential gains that can be obtained from lying. Side-payment schemes (monetary rewards for submitted feedback) can make truth-telling rational based on the correlation between the reports of different buyers. In this paper we use the idea of automated mechanism design to construct the payments that minimize the budget required by an incentive-compatible reputation mechanism. Such payment schemes are defined by a linear optimization problem that can be solved efficiently in realistic settings. Furthermore, we investigate two directions for further lowering the cost of incentive-compatibility: using several reference reports to construct the side-payments, and filtering out reports that are probably false.

There is growing evidence that consumers are influenced by Internet-based opinion forums before making a variety of purchase decisions. Firms whose products are being discussed in such forums are therefore tempted to manipulate consumer perceptions by posting costly anonymous messages that praise their products. This paper offers a theoretical analysis of the impact of such behavior on firm profits and consumer surplus. There are three main results. First, if every firm’s manipulation strategy is a monotonically increasing (decreasing) function of that firm’s true quality, strategic manipulation of online forums increases (decreases) the information value of a forum to consumers. This result implies the existence of settings where online forum manipulation benefits consumers. Second, equilibria where strategies are monotonically increasing (decreasing) functions of a firm’s true quality exist in settings where the firm’s net payoff function, inclusive of the cost of manipulation, is supermodular (submodular) in the firm’s quality and manipulation action. Third, in a broad class of settings, if the precision of honest consumer opinions that firms manipulate is sufficiently high, firms of all types, as well as society, would be strictly better off if manipulation of online forums was not possible. Nonetheless, firms are locked into a “rat race” and forced to spend resources on such profit-reducing activities; if they don’t, consumer perceptions will be biased against them. The social cost of online manipulation can be reduced by developing “filtering” technologies that make it costlier for firms to manipulate. Interestingly, as the amount of user-contributed online content increases, it is firms, and not consumers, that have most to gain from the development of such technologies.

Abstract. Most web services need to be contracted through service level agreements that typically specify a certain quality of service (QoS) in return for a certain price. We propose a new form of service level agreement where the price is determined by the QoS actually delivered. We show that such agreements make it optimal for the service provider to deliver the service at the promised quality. To allow efficient monitoring of the actual QoS, we introduce a reputation mechanism. A scoring rule makes it optimal for the users of a service to correctly report the QoS they observed. Thus, we obtain a practical scheme for service-level agreements that makes it uninteresting for providers to deviate from their best effort. 1

Service-level agreements (SLAs) establish a contract between service providers and clients concerning Quality of Service (QoS) parameters. Without proper penalties, service providers have strong incentives to deviate from the advertised QoS, causing losses to the clients. Reliable QoS monitoring (and proper penalties computed on the basis of delivered QoS) are therefore essential for the trustworthiness of a service-oriented environment. In this paper, we present a novel QoS monitoring mechanism based on quality ratings from the clients. A reputation mechanism collects the ratings and computes the actual quality delivered to the clients. The mechanism provides incentives for the clients to report honestly, and pays special attention to minimizing cost and overhead. 1

Abstract. We commonly use the experience of others when taking decisions. Reputation mechanisms aggregate in a formal way the feedback collected from peers and compute the reputation of products, services, or providers. The success of reputation mechanisms is however conditioned on obtaining true feedback. Side-payments (i.e. agents get paid for submitting feedback) can make honest reporting rational (i.e. Nash equilibrium). Unfortunately, known schemes also have other Nash equilibria that imply lying. In this paper we analyze the equilibria of two incentive-compatible reputation mechanisms and investigate how undesired equilibrium points can be eliminated by using trusted reports. 1

Reputation mechanisms offer an effective alternative to verification authorities for building trust in electronic markets with moral hazard. Future clients guide their business decisions by considering the feedback from past transactions; if truthfully exposed, cheating behavior is sanctioned and thus becomes irrational. It therefore becomes important to ensure that rational clients have the right incentives to report honestly. As an alternative to side-payment schemes that explicitly reward truthful reports, we show that honesty can emerge as a rational behavior when clients have a repeated presence in the market. To this end we describe a mechanism that supports an equilibrium where truthful feedback is obtained. Then we characterize the set of paretooptimal equilibria of the mechanism, and derive an upper bound on the percentage of false reports that can be recorded by the mechanism. An important role in the existence of this bound is played by the fact that rational clients can establish a reputation for reporting honestly.

Efficiently handling reputation is important in dealing with free-riding, malicious attacks and random failures in selforganized communication systems. At the same time, work in this context is often found to be relevant in many other disciplines, in particular the social sciences. A number of distributed reputation systems have been proposed and analyzed, although research has not been very coherent. In this paper, for the first time, we provide an overview of the stateof-the-art in the various computer science communities as well as the social sciences. In particular, we present results obtained from our mathematical model devised to investigate the impact of liars on their peers ’ reputation about a subject. We find that liars have no impact unless their number exceeds a certain threshold (phase transition). We give precise formulae and quantify the impact, thereby providing insight into fundamental questions in social networks as well as facilitating performance evaluation and optimization of distributed reputation systems in communication networks. We conclude by suggesting fundamental directions for future research into reputation. Categories and Subject Descriptors C.2.1 [Computer-communication networks]: Network architecture and design—Distributed networks; D.2.4 [Computer-communication networks]: Distributed systems—

Bayesian game theory in practice: A framework for online reputation systems

Recently, online reputation mechanisms have been proposed that reward agents for honest feedback about products and services with fixed quality. Many real-world settings, however, are inherently dynamic. As an example, consider a web service that wishes to publish the expected download speed of a file mirrored on different server sites. In contrast to the models of Miller, Resnick and Zeckhauser and of Jurca and Faltings, the quality of the service (e. g., a server’s available bandwidth) changes over time and future agents are solely interested in the present quality levels. We show that hidden Markov models (HMM) provide natural generalizations of these static models and design a payment scheme that elicits honest reports from the agents after they have experienced the quality of the service. 1

The most prominent way to establish trust between buyers and sellers on online auction sites are reputation mechanisms. Two drawbacks of this approach are the reliance on the seller being long-lived and the susceptibility to whitewashing. In this paper, we introduce so-called escrow mechanisms that avoid these problems by installing a trusted intermediary which forwards the payment to the seller only if the buyer acknowledges that the good arrived in the promised condition. We address the incentive issues that arise and design an escrow mechanism that is incentive compatible, efficient, interim individually rational and ex ante budget-balanced. In contrast to previous work on trust and reputation, our approach does not rely on knowing the sellers ’ cost functions or the distribution of buyer valuations.