1. A method of selecting an optimum factor for use in estimating characteristics of a plurality of viewers who view a same content, the method being implemented by a computer including a processor and a memory, the method comprising: storing in the memory, by the processor, a multi-layered hierarchal factor-list of a plurality of pre-selected factors each of which is a candidate of the optimum factor, the factors being a plurality of attribute words which express attributes of the viewers, the factor list having a plurality of layers; storing in the memory, by the processor, a plurality of sets of learned-text information which are relevant to the plurality of attribute words, in sections, on a per-attribute-word basis, the sets of learned-text information including a plurality of comments which were published by the plurality of viewers, the comments being relevant to the context of the same content; extracting, by the processor, a plurality of keywords from the same content; generating, by the processor, a first vector indicative of frequencies with which the plurality of keywords occur in the same content, the first vector having a plurality of elements which the plurality of keywords are allocated, respectively, the elements having values indicative of the frequencies of the plurality of keywords, respectively; for a successively-selected one of the keywords, successively generating, by the processor, a second vector indicative of frequencies with which the plurality of keywords occur in ones of the plurality of sets of learned-text information which ones contain an attribute word identical with the successively-selected keyword, the second vector having a plurality of elements which the plurality of keywords are allocated, respectively, the elements having values indicative of the frequencies of the plurality of keywords, respectively; calculating, by the processor, a similarity score between the first and second vectors on a per-keyword basis; successively (1) selecting, by the processor, one of the plurality of layers from the factor list, by moving through the plurality of layers of the factor list in a direction from a top-most layer to a bottom-most layer, and on a per-layer basis, (2) selecting, by the processor, one of the plurality of factors as the optimum factor, wherein the one factor is associated with a sub-plurality of attribute words, which are on a lower layer than that of the one factor, and coincident with at least some of the plurality of keywords, so that a dispersion level indicative of how the similarity scores calculated for the sub-plurality of attribute words are dispersed therewithin can be substantially the maximum among the plurality of factors on the same layer, and (3) selecting, by the processor, the sub-plurality of attribute words as optimum attribute words for the optimum factor; and analyzing, by the processor, the comments based on the selected optimum factor, thereby segmenting the plurality of viewers based on the selected optimum factor to estimate the viewers' characteristics.
3. The method according to claim 1 , wherein the extracting includes performing morphological analysis for a text part of the same content, to thereby extract the plurality of keywords from the text part, and optionally includes calculating a TF-IDF (Term Frequency-Inverse Document Frequency) score for each of the extracted key words, to thereby select at least one of the extracted keywords which is more distinct from any other keyword, each as a final keyword.