Crowdsourcing is characterized by the externalization of tasks to a crowd of workers. The crowd is very diversified due to tasks simplicity, but the payment attract malicious workers. It is essential to identify these malicious workers in order not to consider their answers. In addition, not all workers have the same qualification for a task, so it might be interesting to give more weight to those with more qualifications. This paper, published during the ICTAI 2019 conference, proposes a method for characterizing the profile of contributors and aggregating answers using the theory of belief functions to estimate uncertain and imprecise answers.