Reputation system

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A reputation system is a type of collaborative filtering algorithm which attempts to determine ratings for a collection of entities, given a collection of opinions that those entities hold about each other. This is similar to a recommendation system, but with the purpose of entities recommending each other, rather than some external set of entities (such as books, movies, or music).

Reputation systems are often useful in large online communities in which users may frequently have the opportunity to interact with users with whom they have no prior experience or in communities where user generated content is posted like YouTube or Flickr. In such a situation, it is often helpful to base the decision whether or not to interact with that user on the prior experiences of other users.

Reputation systems may also be coupled with an incentive system to reward good behavior and punish bad behavior. For instance, users with high reputation may be granted special privileges, whereas users with low or unestablished reputation may have limited privileges.

[edit] Types of reputation systems

A simple reputation system, employed by eBay, is to record a rating (either positive, negative, or neutral) after each pair of users conducts a transaction. A user's reputation comprises the count of positive and negative transactions in that user's history.

More sophisticated algorithms scale an individual entity's contribution to other node's reputation by that entity's own reputation. PageRank is such a system, used for ranking web pages based on the link structure of the web. In PageRank, each web page's contribution to another page is proportional to its own pagerank, and inversely proportional to its number of outlinks.

Reputation systems are also emerging which provide a unified, and in many cases objective, appraisal of the impact to reputation of a particular news item, story, blog or online posting. The systems also utilize complex algorithms to firstly capture the data in question but then rank and score the item as to whether it improves or degrades the reputation of the individual, company or brand in question.

[edit] Online reputation systems

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 inclines that these systems arose as a result of the need for internet users to gain trust in the individuals they transact with online. The innate trait he makes note of in humans is that functions of society 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 service this consumer 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'.

[edit] Other examples of practical applications

[edit] Attacks on reputation systems

A Sybil attack is one in which an attacker subverts the reputation system by creating a large number of pseudonymous entities, and using them to gain a disproportionately large influence. A reputation system's vulnerability to a Sybil attack depends on how cheaply Sybils can be generated, the degree to which the reputation system accepts input from entities that do not have a chain of trust linking them to a trusted entity, and whether the reputation system treats all entities identically. It is named after the subject of the book Sybil, a case study of a woman with multiple personality disorder.

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[edit] External links

Retrieved from "http://en.wikipedia.org/wiki/Reputation_system"
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