Reputation systems for open collaboration

Abstract

Algorithmic-based user incentives ensure the trustworthiness of evaluations of Wikipedia entries and Google Maps business information.

Quality Control in Crowdsourcing Systems: Issues and Directions

“…10 Reputation scores are mainly built on community members' feedback about workers' activities in the system. 11 Sometimes, this feedback is explicit -that is, community members explicitly cast feedback on a worker's quality or contributions by, for instance, rating or ranking the content the worker has created. In other cases, feedback is cast implicitly, as in Wikipedia, when subsequent editors preserve the changes a particular worker has made.…”

Extraction of Hidden Social Networks from Wiki-Environment Involved in Information Conflict

“…WikiTrust was also focused to identify vandalized encyclopedic articles. Here the acts of vandalism are identified by the activity of anonyms (users acting without registration) and new users, who are just registered [16,17].…”

Reducing the History in Decentralized Interaction-Based Reputation Systems

“…In decentralized systems, like BarterCast, where each node stores and analyzes data locally using, e.g., the max-flow algorithm (with complexity O(nm 2 ) where n is the number of nodes and m and the number of edges), even much smaller graphs of 10 6 nodes make the computation of reputations prohibitive. Taking into account that the contributions of nodes in the computation of reputations are not equal in quality and quantity [8], thus we aim to delete the least important contributions and compute reputations using only a subset of the complete history. In this way, we can reduce the computational cost significantly without decreasing the accuracy very much.…”

“…A family of reputation systems useful in many Internet applications consists of interaction-based systems (also called content-driven systems [8]). These systems are based on algorithms analyzing all interactions among users and computing the reputations without using any explicit feedback from users, such as PageRank [18] for ranking web pages and Bartercast [17] for computing reputations of users in P2P systems.…”