Opinion Aggregation

Opinion aggregation focuses on combining multiple opinions or data points to reach a more reliable and informed consensus, addressing challenges like bias and uncertainty. Current research explores various model architectures, including Bayesian methods, linear and logarithmic opinion pools, and adaptations of the Dawid-Skene model, to improve accuracy and fairness while mitigating cognitive biases and managing uncertainty in diverse contexts such as social networks and multi-criteria assessments. These advancements are significant for improving decision-making in fields ranging from crowdsourcing and cyber threat attribution to social science and machine learning, offering more robust and reliable results.