Reputation system

Reputation systems are programs that allow users to rate each other in online communities in order to build trust through reputation. Some common uses of these systems can be found on E-commerce websites such as eBay, Amazon.com, and Etsy as well as online advice communities such as Stack Exchange. These reputation systems represent a significant trend in 'decision support for Internet mediated service provisions'. With the popularity of online communities for shopping, advice, and exchange of other important information, reputation systems are becoming vitally important to the online experience. The idea of reputations systems is that even if the consumer can't physically try a product or service, or see the person providing information, that they can be confident in the outcome of the exchange through trust built by recommender systems. Reputation systems are programs that allow users to rate each other in online communities in order to build trust through reputation. Some common uses of these systems can be found on E-commerce websites such as eBay, Amazon.com, and Etsy as well as online advice communities such as Stack Exchange. These reputation systems represent a significant trend in 'decision support for Internet mediated service provisions'. With the popularity of online communities for shopping, advice, and exchange of other important information, reputation systems are becoming vitally important to the online experience. The idea of reputations systems is that even if the consumer can't physically try a product or service, or see the person providing information, that they can be confident in the outcome of the exchange through trust built by recommender systems. Collaborative filtering, used most commonly in recommender systems, are related to reputation systems in that they both collect ratings from members of a community. The core difference between reputation systems and collaborative filtering is the ways in which they use user feedback. In collaborative filtering, the goal is to find similarities between users in order to recommend products to customers. The role of reputation systems, in contrast, is to gather a collective opinion in order to build trust between users of an online community. Howard Rheingold states that online reputation systems are 'computer-based technologies that make it possible to manipulate in new and powerful ways an old and essential human trait'. Rheingold says that these systems arose as a result of the need for Internet users to gain trust in the individuals they transact with online. The trait he notes in human groups is that social functions such as gossip 'keeps us up to date on who to trust, who other people trust, who is important, and who decides who is important'. Internet sites such as eBay and Amazon, he argues, seek to make use of this social trait and are 'built around the contributions of millions of customers, enhanced by reputation systems that police the quality of the content and transactions exchanged through the site'. The emerging sharing economy increases the importance of trust in peer-to-peer marketplaces and services. Users can build up reputation and trust in individual systems but usually don't have the ability to carry those reputations to other systems. Rachel Botsman and Roo Rogers argue in their book What's Mine is Yours (2010), that 'it is only a matter of time before there is some form of network that aggregates reputation capital across multiple forms of Collaborative Consumption'. These systems, often referred to as reputation banks, try to give users a platform to manage their reputation capital across multiple systems. The main function of reputation systems is to build a sense of trust among users of online communities. As with brick and mortar stores, trust and reputation can be built through customer feedback. Paul Resnick from the Association of Computing Machinery describes three properties that are necessary for reputation systems to operate effectively.