Abstract
The important word was able to be extracted from text mining about the free description column of a city planning questionnaire. Moreover, the character of the word which contributes to city planning was extracted from the cooccurrence relation of the word.The target field is the public underground space of Shonandai-station in Fujisawa city, Kanagawa prefecture. Free description from the citizen request about station underground space was analyzed by text mining.We specified some important requests about a store, an event, escalator, an elevator, a bicycle, etc.