eprintid: 1499907 rev_number: 29 eprint_status: archive userid: 608 dir: disk0/01/49/99/07 datestamp: 2016-06-19 00:48:33 lastmod: 2021-10-16 22:08:03 status_changed: 2017-06-20 10:02:52 type: article metadata_visibility: show creators_name: Livan, G creators_name: Caccioli, F creators_name: Aste, T title: Excess reciprocity distorts reputation in online social networks ispublished: pub divisions: UCL divisions: B04 divisions: C05 divisions: F48 note: 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/. © The Author(s) 2017 abstract: 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. date: 2017-06-14 date_type: published official_url: http://dx.doi.org/10.1038/s41598-017-03481-7 oa_status: green full_text_type: pub language: eng primo: open primo_central: open_green article_type_text: Journal Article verified: verified_manual elements_id: 1134158 doi: 10.1038/s41598-017-03481-7 pii: 10.1038/s41598-017-03481-7 lyricists_name: Aste, Tomaso lyricists_name: Caccioli, Fabio lyricists_name: Livan, Giacomo lyricists_id: TASTE72 lyricists_id: FCACC19 lyricists_id: GLIVA46 actors_name: Dewerpe, Marie actors_id: MDDEW97 actors_role: owner full_text_status: public publication: Science Reports volume: 7 number: 1 article_number: 3551 event_location: England issn: 2045-2322 citation: Livan, G; Caccioli, F; Aste, T; (2017) Excess reciprocity distorts reputation in online social networks. Science Reports , 7 (1) , Article 3551. 10.1038/s41598-017-03481-7 <https://doi.org/10.1038/s41598-017-03481-7>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/1499907/1/Aste_art%25253A10.1038%25252Fs41598-017-03481-7.pdf