@techreport{79367bdcb3f84f909a96819fb2f9bfab,
title = "屋敷林所有者の意識に及ぼす地理的条件の影響: テキストマイニングによる可視化の試み",
abstract = "Text mining (TM) is a relatively new method of quantitative analysis of large-scale document data. it has been widely used as a powerful tool to visualize the semantic connections between words in document data, and to identify potential trends and characteristics of the data. It has been widely used as a tool to elucidate potential trends and characteristics of the data. By using TM to analyse the free response section, which is often included in large-scale attitude surveys but rarely analysed quantitatively, we can extract and visualise latent response tendencies and dramatically increase the knowledge gained. Therefore, this study will apply TM to the free answers of the attitude survey to the owners of house forests conducted by Tonami City, and visualize the latent tendency, in order to (1) examine the latent influence of geographical conditions on the answers, and (2) find out the latent tendency of the answers which has been omitted from the quantitative analysis in the large-scale attitude surveys conducted by many municipalities in Japan.",
author = "M Kawai and K Asano and K Suzuki",
note = "Is international journal: false",
year = "2022",
month = may,
language = "日本",
volume = "39",
series = "砺波散村地域研究所研究紀要",
publisher = "砺波市立砺波散村地域研究所",
pages = "33--43",
type = "WorkingPaper",
institution = "砺波市立砺波散村地域研究所",
}