  Worker selection is a significant and challenging issue in crowdsourcing
systems. Such selection is usually based on an assessment of the reputation of
the individual workers participating in such systems. However, assessing the
credibility and adequacy of such calculated reputation is a real challenge. In
this paper, we propose an analytic model which leverages the values of the
tasks completed, the credibility of the evaluators of the results of the tasks
and time of evaluation of the results of these tasks in order to calculate an
accurate and credible reputation rank of participating workers and fairness
rank for evaluators. The model has been implemented and experimentally
validated.
