Enhancing Public Reputation Systems: Trust Scaling to Mitigate Voter Subjectivity

In the digital age, the reliability of public reputation systems is increasingly challenged by the subjectivity of voter assessments. This paper presents a novel public reputation estimation method that leverages a scaling trust framework to mitigate the influence of individual biases and enhance the accuracy of reputation scores. We propose a scaling mechanism that adjusts the weight of each voter’s input according to their trustworthiness, thereby reducing the impact of outlier opinions and fostering a more balanced representation of public sentiment. The experiment results demonstrate that our method significantly improves the robustness and fairness of reputation estimations compared to traditional models.