1. A computer-implemented method for performing contextual classification of objects, comprising: receiving supervised training data transmitted over a network from at least one content reviewer; storing the supervised training data in a database; preprocessing, with at least one processor, the supervised training data to form at least one vectorized object; training a plurality of models by applying a plurality of machine learning algorithms to the at least one vectorized object; identifying, with at least one processor, an optimal model from the plurality of models; and classifying a candidate object using the identified optimal model.