A Model for Citizen Scientist Contribution in an Image Tagging Task

Citizen science projects are becoming increasingly popular, yet they typically rely on only a small portion of users for the majority of contribution. In this paper, we propose a model for citizen scientist contribution in an online image tagging task. The model describes participant contribution in response to the performance of a virtual peer, the behavior of which can be controlled by the experimenter. Experimental trials where the virtual peer behaves independent of the participant are used to calibrate the model. The model’s ability to predict participant performance is then verified in a closed-loop condition, where the behavior of the virtual peer is explicitly dependant on the performance of the participant. We foresee this model being a useful tool in the design of web-based citizen science projects, where the behavior of a virtual peer can be used to modulate the performance of contributors in an effort to increase overall levels of contribution.