1. A computer-implemented method comprising: sending each proposal of a plurality of proposals at a different time to a client device of a user, the proposal comprising a respective request for the user to translate a respective text message and a respective incentive for the translation; receiving from the client device a plurality of translations authored by the user, each translation being associated with one of the proposals and being a translation of the text message of the associated proposal; for each proposal, comparing a plurality of features associated with the text message with a respective plurality of features associated with the translation to generate respective feature scores, the features comprising word-based features, language-based features, word alignment features, and combinations thereof, and calculating an accuracy based on a weighted combination of the respective feature scores wherein the weights are derived using a statistical regression to model accuracy of translations; identifying a deviation from a norm in user translation accuracy over a period of time based on the calculated accuracies; updating a confidence score for the user based on the deviation in user translation accuracy; and revoking the translation privileges of the user when the confidence score does not satisfy a threshold value.