ACitizen science projects are becoming increasingly popular, yet they typically rely on only a small portion of users for the ma- jority of contribution. In this paper, we propose a model for cit- izen scientist contribution in an online image tagging task. The model describes participant contribution in response to the per- formance of a virtual peer, the behavior of which can be con- trolled by the experimenter. Experimental trials where the vir- tual peer behaves independent of the participant are used to cal- ibrate the model. The model's ability to predict participant per- formance is then verified in a closed-loop condition, where the behavior of the virtual peer is explicitly dependant on the perfor- mance 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 per- formance of contributors in an effort to increase overall levels of contribution.