Trust and reputation systems represent a significant trend in decision support for Internet mediated service provision. The basic idea is to let parties rate each other, for example after the completion of a transaction, and use the aggregated ratings about a given party to derive a trust or reputation score, which can assist other parties in deciding whether or not to transact with that party in the future. A natural side effect is that it also provides an incentive for good behaviour, and therefore tends to have a positive effect on market quality. Reputation systems can be called collaborative sanctioning systems to reflect their collaborative nature, and are related to collaborative filtering systems. Reputation systems are already being used in successful commercial online applications. There is also a rapidly growing literature around trust and reputation systems, but unfortunately this activity is not very coherent. The purpose of this article is to give an overview of existing and proposed systems that can be used to derive measures of trust and reputation for Internet transactions, to analyse the current trends and developments in this area, and to propose a research agenda for trust and reputation systems.

@article{jsang2007survey, author = {Jøsang, Audun and Ismail, Roslan and Boyd, Colin}, title = {A survey of trust and reputation systems for online service provision}, journal = {Decision Support Systems}, year = {2007}, volume = {43}, number = {2}, pages = {618 - 644}, note = {Emerging Issues in Collaborative Commerce}, url = {http://www.sciencedirect.com/science/article/pii/S0167923605000849}, doi = {10.1016/j.dss.2005.05.019}, issn = {0167-9236}, keywords = {bayesian, reputation, online, info20, average, aggregation}, abstract = {Trust and reputation systems represent a significant trend in decision support for Internet mediated service provision. The basic idea is to let parties rate each other, for example after the completion of a transaction, and use the aggregated ratings about a given party to derive a trust or reputation score, which can assist other parties in deciding whether or not to transact with that party in the future. A natural side effect is that it also provides an incentive for good behaviour, and therefore tends to have a positive effect on market quality. Reputation systems can be called collaborative sanctioning systems to reflect their collaborative nature, and are related to collaborative filtering systems. Reputation systems are already being used in successful commercial online applications. There is also a rapidly growing literature around trust and reputation systems, but unfortunately this activity is not very coherent. The purpose of this article is to give an overview of existing and proposed systems that can be used to derive measures of trust and reputation for Internet transactions, to analyse the current trends and developments in this area, and to propose a research agenda for trust and reputation systems.} }

%0 = article %A = Jøsang, Audun and Ismail, Roslan and Boyd, Colin %D = 2007 %T = A survey of trust and reputation systems for online service provision %U = http://www.sciencedirect.com/science/article/pii/S0167923605000849

@inproceedings{Whitby04filteringout, author = {Whitby, Andrew and Jøsang, Audun and Indulska, Jadwiga}, title = {Filtering Out Unfair Ratings in Bayesian Reputation Systems}, year = {2004}, keywords = {review, Filtering, unfair, bayes, rating, reputation, info20} }

%0 = inproceedings %A = Whitby, Andrew and Jøsang, Audun and Indulska, Jadwiga %D = 2004 %T = Filtering Out Unfair Ratings in Bayesian Reputation Systems