1. An analysis device for determining a scale of a response of one or more individuals to a future event, said device comprising: a memory; one or more processor devices associated with the memory, said one or more processor devices configured to: receive data representing a history of events associated with an individual, said history of events arranged in a time series over a period of time; substitute each event in each of the one or more event time series with rectangular windows of predetermined time width; divide the event series timewise according to transition points corresponding to beginning timestamps and end timestamps associated with each of the rectangular windows to obtain multiple adjacent time periods; generate a state vector corresponding to the state of the rectangular windows in each of the multiple adjacent time periods; calculate a response frequency for each time period, the response frequency being the number of responses generated during the time period; convert the state vectors to feature vectors; perform a Poisson regression using the state vectors and the response frequencies corresponding to the time periods, optimize a weight vector to maximize a likelihood with which response frequencies can be obtained in the time periods from a Poisson distribution on the basis of a scalar score obtained from the scalar product of the feature vectors and the weight vector, store in the memory, the optimized weight vector for the individual; and determine a response characteristic of the individual to a future event series using the stored weight vector.