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Reputation is a valuable asset in online social lives and it has drawnincreased attention. How to evaluate user reputation in online rating systemsis especially significant due to the existence of spamming attacks. To addressthis issue, so far, a variety of methods have been proposed, includingnetwork-based methods, quality-based methods and group-based ranking method. Inthis paper, we propose an iterative group-based ranking (IGR) method byintroducing an iterative reputation-allocation process into the originalgroup-based ranking (GR) method. More specifically, users with higherreputation have higher weights in dominating the corresponding group sizes. Thereputation of users and the corresponding group sizes are iteratively updateduntil they become stable. Results on two real data sets suggest that theproposed IGR method has better performance and its robustness is considerablyimproved comparing with the original GR method. Our work highlights thepositive role of users' grouping behavior towards a better reputationevaluation.

Evaluating user reputation in online rating systems via an iterative group-based ranking method