SLoT Map is the town map that integrates the collective information of snapshots (S), their locations (Lo) and the descriptive texts (T). It is constructed by the two stage procedure: classification of snapshots and locations, and correspondence analysis of words in the texts. The additional information on the classification stabilizes the analysis of sparse matrix peculiar to the text-mined data. By using collective intelligence, SLoT Map method can translate subjective individual impressions into rather an objective comprehensive expression. We demonstrate the efficiency of the procedure by the SLoT Map around Hongo area in Tokyo.
