1. A method for computing token-dependent affective response baseline levels for a user, comprising: receiving a certain temporal window of token instances; receiving, from a database, first and third affective response annotations corresponding to first and third temporal windows of token instances, respectively; wherein the database further stores a second affective response annotation corresponding to a second temporal window of token instances, the user was exposed to the first, second, and third, temporal windows of token instances during first, second, and third time periods, respectively; and wherein the first time period precedes the second time period, and the second time period precedes the third time period; using a distance function, calculating a first metric, a second metric, and a third metric between the certain temporal window of token instances and of the first temporal window of token instances, the second temporal window of token instances, and the third temporal window of token instances, respectively; wherein the first and third metrics are below a predefined threshold, while the second metric is not below the predefined threshold; computing a first affective response baseline level associated with the certain temporal window of token instances based on data comprising the first and third affective response annotations; receiving an additional temporal window of token instances; receiving, from the database, the second affective response annotation; wherein a fourth metric between the additional temporal window of token instances and the second temporal window of token instances is below the predefined threshold; and computing a second affective response baseline level associated with the additional temporal window of token instances based on data comprising the second affective response annotation; wherein the computed first affective response baseline level is different from the computed second affective response baseline level; wherein the first and second affective response baseline levels each represent a value comprising at least one of: an emotional response, and a value of a user measurement channel.
3. The method of claim 1 , further comprising generating a sample from data comprising: the affective response first baseline level and the certain temporal window of token instances; and providing the sample to a machine learning predictor to predict affective response of the user to the certain temporal window of token instances.