1. A method comprising: receiving, by a computer system, emotion sensor data for a plurality of contexts from a plurality of distributed electronic devices, wherein each of the plurality of contexts corresponds to one or more of a geographical area and a time period, wherein the emotion sensor data comprises implicit emotion indicators based on information sensed by the plurality of distributed electronic devices for the plurality of contexts, wherein the emotion sensor data further comprises explicit emotion descriptors based on user reported descriptions of emotions for the plurality of contexts; determining, by the computer system, a first context in the plurality of contexts; determining, by the computer system, a first portion of the emotion sensor data determined to be received from a first portion of the plurality of distributed electronic devices, wherein the first portion of the emotion sensor data is based on information sensed for the first context; generating, by the computer system, a first emotion profile for the first context based on the first portion of the emotion sensor data, the generating comprising weighting the implicit emotion indicators differently from the explicit emotion descriptors based at least on a reliability, tracking, using an emotion trend profile, an emotional change associated with a move from one of the plurality of contexts to another of the plurality of contexts; and predicting, using the emotion trend profile and the first emotion profile, a predicted emotional change associated with a move from one of the plurality of contexts to the first context; wherein the first emotion profile comprises a description of a first emotion associated with the first context, and wherein the computer system comprises one or more computer processors configured to perform the steps of the method.
15. The method of claim 1 , wherein the first context comprises a dynamically determined geographical region in which the first portion of the plurality of distributed electronic devices were located to sense the information on which the emotion sensor data is based.