1. A data analyzer that executes data analysis using a “Spreading Activation Theory” method, the data analyzer comprising: a computer-readable storage unit that stores data values at any one of N stages (N is an integer not smaller than 2) while associating the data values with a plurality of data elements respectively and stores association weighting information among the data elements, the data elements being selected using a stemming process; a selecting and computing unit that selects one of the data elements as a target data on the basis of a predetermined rule and computes an input stimulus value concerned with the target data on the basis of the association weighting information between the target data and the other data elements and the data values of the other data elements; and an updating unit that updates the data value of the target data on the basis of the computed input stimulus value in such a manner that a threshold decided in accordance with a current data value associated with the target data and varying according to each data value is compared with the input stimulus value to determine whether the data value needs to be changed or not, and that the data value is updated when a decision is made that the data value needs to be changed, wherein after repeating execution of computing of the input stimulus value and updating of the data value until satisfaction of a predetermined condition, the data value concerned with at least one of the data elements is subjected to a predetermined process.