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Excess reciprocity distorts reputation in online social networks

The peer-to-peer (P2P) economy relies on establishing trust in distributed networked systems, where the reliability of a user is assessed through digital peer-review processes that aggregate ratings into reputation scores. Here we present evidence of a network effect which biases digital reputation,...

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Detalles Bibliográficos
Autores principales: Livan, Giacomo, Caccioli, Fabio, Aste, Tomaso
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5471239/
https://www.ncbi.nlm.nih.gov/pubmed/28615619
http://dx.doi.org/10.1038/s41598-017-03481-7
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author Livan, Giacomo
Caccioli, Fabio
Aste, Tomaso
author_facet Livan, Giacomo
Caccioli, Fabio
Aste, Tomaso
author_sort Livan, Giacomo
collection PubMed
description The peer-to-peer (P2P) economy relies on establishing trust in distributed networked systems, where the reliability of a user is assessed through digital peer-review processes that aggregate ratings into reputation scores. Here we present evidence of a network effect which biases digital reputation, revealing that P2P networks display exceedingly high levels of reciprocity. In fact, these are much higher than those compatible with a null assumption that preserves the empirically observed level of agreement between all pairs of nodes, and rather close to the highest levels structurally compatible with the networks’ reputation landscape. This indicates that the crowdsourcing process underpinning digital reputation can be significantly distorted by the attempt of users to mutually boost reputation, or to retaliate, through the exchange of ratings. We uncover that the least active users are predominantly responsible for such reciprocity-induced bias, and that this fact can be exploited to obtain more reliable reputation estimates. Our findings are robust across different P2P platforms, including both cases where ratings are used to vote on the content produced by users and to vote on user profiles.
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spelling pubmed-54712392017-06-19 Excess reciprocity distorts reputation in online social networks Livan, Giacomo Caccioli, Fabio Aste, Tomaso Sci Rep Article The peer-to-peer (P2P) economy relies on establishing trust in distributed networked systems, where the reliability of a user is assessed through digital peer-review processes that aggregate ratings into reputation scores. Here we present evidence of a network effect which biases digital reputation, revealing that P2P networks display exceedingly high levels of reciprocity. In fact, these are much higher than those compatible with a null assumption that preserves the empirically observed level of agreement between all pairs of nodes, and rather close to the highest levels structurally compatible with the networks’ reputation landscape. This indicates that the crowdsourcing process underpinning digital reputation can be significantly distorted by the attempt of users to mutually boost reputation, or to retaliate, through the exchange of ratings. We uncover that the least active users are predominantly responsible for such reciprocity-induced bias, and that this fact can be exploited to obtain more reliable reputation estimates. Our findings are robust across different P2P platforms, including both cases where ratings are used to vote on the content produced by users and to vote on user profiles. Nature Publishing Group UK 2017-06-14 /pmc/articles/PMC5471239/ /pubmed/28615619 http://dx.doi.org/10.1038/s41598-017-03481-7 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Livan, Giacomo
Caccioli, Fabio
Aste, Tomaso
Excess reciprocity distorts reputation in online social networks
title Excess reciprocity distorts reputation in online social networks
title_full Excess reciprocity distorts reputation in online social networks
title_fullStr Excess reciprocity distorts reputation in online social networks
title_full_unstemmed Excess reciprocity distorts reputation in online social networks
title_short Excess reciprocity distorts reputation in online social networks
title_sort excess reciprocity distorts reputation in online social networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5471239/
https://www.ncbi.nlm.nih.gov/pubmed/28615619
http://dx.doi.org/10.1038/s41598-017-03481-7
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