A user may be exposed to multiple token instances representing stimuli that may influence the affective state of the user. Described herein are embodiments of systems, method, and computer programs for estimating affective response to a token instance of interest, selected from among the token instances. The token instance of interest is selected based on attention levels received from an external source such as, information received from other users, information received from analysis of communications of the users, and/or information received from an external site such as an online retailer or a social network. In one example embodiment, the token instance of interest is a token instance for which attention level of the user is higher than at least one other token instance.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A system configured to utilize attention levels received from an external source to estimate affective response to a token instance of interest, comprising: a memory configured to store: a total affective response of a user to token instances to which the user was exposed, and representations of first and second attention levels in respective first and second token instances from among the token instances; wherein the first and second attention levels are received from an external source and are not derived from values of a user measurement channel of the user; wherein the first and second token instances have overlapping instantiation periods; and wherein the first attention level is greater than the second attention level; a processor configured to select, based on the representations of the first and second attention levels, the first token instance as the token instance of interest; and the processor is further configured to estimate the affective response to the token instance of interest from the total affective response. 2. The system of claim 1, wherein the total affective response is based, at least in part, on a value of a user measurement channel of the user. 3. The system of claim 1, wherein the first and second attention levels are derived from answers to questions, provided by one or more users, which indicate areas of interest of the user. 4. The system of claim 1, wherein the first and second attention levels are generated utilizing semantic analysis of communications of the user. 5. The system of claim 4, wherein the communications comprise at least one of: voice conversations, video conversations, instant messages, emails, posts to social media, search queries, and browsing history. 6. The system of claim 1, wherein the first and second attention levels are received from a third party comprising at least one of: a social networking site and an online retailer. 7. The system of claim 1, wherein the total affective response is expressed as an emotional response. 8. The system of claim 1, wherein the total affective response is expressed as a value of a user measurement channel of the user. 9. The system of claim 1, wherein the total affective response is proportional to the difference between affective responses of the user before and after the user was exposed to the token instances. 10. The system of claim 1, wherein the memory is further configured to store a baseline value for affective response of the user, and the processor is further configured to calculate the total affective response with respect to the baseline value; whereby the baseline value represents a usual affective response of the user, as computed from multiple values acquired over a period of at least a few hours. 11. The system of claim 1, wherein more than 50% of the total affective response is attributed to the affective response to the token instance of interest. 12. A method for utilizing attention levels received from an external source to estimate affective response to a token instance of interest, comprising: receiving a total affective response of a user to token instances to which the user was exposed; wherein the token instances comprise first and second token instances that have overlapping instantiation periods; receiving representations of first and second attention levels in the first and second token instances, respectively; wherein the first and second attention levels are received from an external source and are not derived from values of a user measurement channel of the user; and wherein the first attention level is greater than the second attention level; selecting, based on the representations of the first and second attention levels, the first token instance as the token instance of interest; and estimating the affective response to the token instance of interest from the total affective response. 13. The method of claim 12, further comprising deriving the first and second attention levels from answers to questions, provided by one or more users, which indicate areas of interest of the user. 14. The method of claim 12, further comprising utilizing semantic analysis of communications of the user in order to generate the first and second attention levels. 15. The method of claim 12, further comprising receiving the first and second attention levels from a third party comprising at least one of: a social networking site and an online retailer. 16. The method of claim 12, further comprising receiving a baseline value for affective response of the user and calculating the total affective response with respect to the baseline value; whereby the baseline value represents a usual affective response of the user, as computed from multiple values acquired over a period of at least a few hours. 17. The method of claim 12, further comprising attributing more than 50% of the total affective response to the token instance of interest. 18. A non-transitory computer-readable medium for use in a computer to utilize attention levels received from an external source to estimate affective response to a token instance of interest; the computer comprises a processor, and the non-transitory computer-readable medium comprising: program code for receiving a total affective response of a user to token instances to which the user was exposed; wherein the token instances comprise first and second token instances that have overlapping instantiation periods; program code for receiving representations of first and second attention levels in the first and second token instances, respectively; wherein the first and second attention levels are received from an external source and are not derived from values of a user measurement channel of the user; and wherein the first attention level is greater than the second attention level; program code for selecting, based on the representations of the first and second attention levels, the first token instance as the token instance of interest; and program code for estimating the affective response to the token instance of interest from the total affective response. 19. The non-transitory computer-readable medium of claim 18, further comprising program code for utilizing semantic analysis of communications of the user in order to generate the first and second attention levels. 20. The non-transitory computer-readable medium of claim 18, further comprising program code for receiving the first and second attention levels from a third party comprising at least one of: a social networking site and an online retailer.