1. A method for training an emotional response predictor to predict a user's emotional state after being exposed to tokens representing stimuli that influence the user's affective state, the method comprising: receiving samples comprising temporal windows of token instances to which the user was exposed; the token instances are spread over a long period of time, and a subset of the token instances originate from a same source and have overlapping instantiation periods; receiving target values, which represent affective response annotations of the user and correspond to the temporal windows of token instances; and training the emotional response predictor on input data comprising the samples and the corresponding target values; wherein the emotional response predictor compensates for non-linear effects resulting from saturation due to the user being exposed to the subset of a plurality of token instances originating from the same source and having overlapping instantiation periods.