Iterative group-based and difference ranking method for online rating systems with spamming attacks

It is significant to assign reputation scores to users and identify spammers in the bipartite rating networks. In this paper, we propose an Iterative Group-based and Difference Ranking (IGDR) method, which is based on the original Iterative Group-based Ranking (IGR) method. The IGR method considers...

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Main Authors: Fu, Quan-Yun, Ren, Jian-Feng, Sun, Hong-Liang
Format: Article
Language:English
Published: World Scientific 2021
Subjects:
Online Access:https://eprints.nottingham.ac.uk/65182/
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author Fu, Quan-Yun
Ren, Jian-Feng
Sun, Hong-Liang
author_facet Fu, Quan-Yun
Ren, Jian-Feng
Sun, Hong-Liang
author_sort Fu, Quan-Yun
building Nottingham Research Data Repository
collection Online Access
description It is significant to assign reputation scores to users and identify spammers in the bipartite rating networks. In this paper, we propose an Iterative Group-based and Difference Ranking (IGDR) method, which is based on the original Iterative Group-based Ranking (IGR) method. The IGR method considers users grouping behaviors, but it ignores the characteristics of the individual ratings. It is discovered that individual rating characteristics could also contribute to the redistribution of reputation scores of users. The user with a smaller rating deviation will be given a higher reputation score. The proposed method outperforms IGR method ranging from 8% to 163% tested on three real datasets. It also can be applied to deal with big data in a short time.
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spelling nottingham-651822021-05-07T08:58:43Z https://eprints.nottingham.ac.uk/65182/ Iterative group-based and difference ranking method for online rating systems with spamming attacks Fu, Quan-Yun Ren, Jian-Feng Sun, Hong-Liang It is significant to assign reputation scores to users and identify spammers in the bipartite rating networks. In this paper, we propose an Iterative Group-based and Difference Ranking (IGDR) method, which is based on the original Iterative Group-based Ranking (IGR) method. The IGR method considers users grouping behaviors, but it ignores the characteristics of the individual ratings. It is discovered that individual rating characteristics could also contribute to the redistribution of reputation scores of users. The user with a smaller rating deviation will be given a higher reputation score. The proposed method outperforms IGR method ranging from 8% to 163% tested on three real datasets. It also can be applied to deal with big data in a short time. World Scientific 2021-01-18 Article PeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/65182/1/output%20%282%29.pdf Fu, Quan-Yun, Ren, Jian-Feng and Sun, Hong-Liang (2021) Iterative group-based and difference ranking method for online rating systems with spamming attacks. International Journal of Modern Physics C . p. 2150059. ISSN 0129-1831 Complex networks; rating networks; spamming attacks http://dx.doi.org/10.1142/S0129183121500595 doi:10.1142/S0129183121500595 doi:10.1142/S0129183121500595
spellingShingle Complex networks; rating networks; spamming attacks
Fu, Quan-Yun
Ren, Jian-Feng
Sun, Hong-Liang
Iterative group-based and difference ranking method for online rating systems with spamming attacks
title Iterative group-based and difference ranking method for online rating systems with spamming attacks
title_full Iterative group-based and difference ranking method for online rating systems with spamming attacks
title_fullStr Iterative group-based and difference ranking method for online rating systems with spamming attacks
title_full_unstemmed Iterative group-based and difference ranking method for online rating systems with spamming attacks
title_short Iterative group-based and difference ranking method for online rating systems with spamming attacks
title_sort iterative group-based and difference ranking method for online rating systems with spamming attacks
topic Complex networks; rating networks; spamming attacks
url https://eprints.nottingham.ac.uk/65182/
https://eprints.nottingham.ac.uk/65182/
https://eprints.nottingham.ac.uk/65182/