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A common form of competition is one where judges grade contestants'performances which are then compiled to determine the final ranking of thecontestants. Unlike in another common form of competition where two contestantsplay a head-to-head match to produce a winner as in football or basketball, theobjectivity of judges are prone to be questioned, potentially undermining thepublic's trust in the fairness of the competition. In this work we show, bymodeling the judge--contestant competition as a weighted bipartite network, howwe can identify biased scores and measure their impact on our inference of thenetwork structure. Analyzing the prestigious International Chopin PianoCompetition of 2015 with a well-publicized scoring controversy as an example,we show that even a single statistically uncharacteristic score can be enoughto gravely distort our inference of the community structure, demonstrating theimportance of detecting and eliminating biases. In the process we also findthat there does not exist a significant system-wide bias of the judges based onthe the race of the contestants.

Jury-Contestant Bipartite Competition Network: Identifying Biased Scores and Their Impact on Network Structure Inference