Wisdom of crowds in computational biology

Evaluating the Wisdom of Crowds

Estimating and forecasting are difficult tasks. This is true whether the activity requires the determination of uncertain future event outcomes, or whether the estimation effort is complex in itself and based on insufficient information. Consequently, such tasks are frequently assigned to experts. Surprisingly, recent research suggests that collectives of non-experts can outperform individual e...

Wisdom of Crowds cluster ensemble

The Wisdom of Crowds is a phenomenon described in social science that suggests four criteria applicable to groups of people. It is claimed that, if these criteria are satisfied, then the aggregate decisions made by a group will often be better than those of its individual members. Inspired by this concept, we present a novel feedback framework for the cluster ensemble problem, which we call Wis...

The Multidimensional Wisdom of Crowds

Distributing labeling tasks among hundreds or thousands of annotators is an increasingly important method for annotating large datasets. We present a method for estimating the underlying value (e.g. the class) of each image from (noisy) annotations provided by multiple annotators. Our method is based on a model of the image formation and annotation process. Each image has different characterist...

Harnessing the Wisdom of Crowds*

We empirically examine the impact of herding on the accuracy of consensus earnings forecasts from a crowd-based platform (Estimize.com). We monitor user information set by tracking user viewing activities and running experiments. We find that the more public information a user views, the less weight she puts on her private information. While this improves the accuracy of individual forecasts, i...

The “Wisdom of Crowds” Effect