紀要論文 会計史研究の傾向の分析におけるテキストマイニングの活用の試み : 『会計史学会年報』1983〜2012年を中心に
Analysis on the Trends of Accounting History Studies Using Text-mining : Focused on Yearbook of Accounting History Association 1983-2012

澤登, 千恵

内容記述
The purpose of this paper is to investigate the trends in the studies of accounting history in Japan through analyzing research papers related to accounting history published in Yearbook of Accounting History Association. This study first identified the overall trends among the research papers from the results obtained through summarizing and analyzing them. In doing so, the following three categorical standards," research field"," region", and" period" were used. In proceeding with the above, in particular, all titles of the research papers were analyzed using text-mining. Frequency tables of words used in the titles were created. Words appearing at high frequency were extracted as keywords. Among the keywords, there were those that included words that could be categorized according to the above three categorical standards. The results of frequency made it possible to predict almost the same trends that were analyzed using these three categorical standards. In addition, categorical standards for keywords that could not be categorized into" research field", "region", and "period" were projected using other categories. The study then investigated whether these other categories could be adopted
The purpose of this paper is to investigate the trends in the studies of accounting history in Japan through analyzing research papers related to accounting history published in Yearbook of Accounting History Association. This study first identified the overall trends among the research papers from the results obtained through summarizing and analyzing them. In doing so, the following three categorical standards," research field"," region", and" period" were used. In proceeding with the above, in particular, all titles of the research papers were analyzed using text-mining. Frequency tables of words used in the titles were created. Words appearing at high frequency were extracted as keywords. Among the keywords, there were those that included words that could be categorized according to the above three categorical standards. The results of frequency made it possible to predict almost the same trends that were analyzed using these three categorical standards. In addition, categorical standards for keywords that could not be categorized into" research field", "region", and "period" were projected using other categories. The study then investigated whether these other categories could be adopted
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https://osu.repo.nii.ac.jp/?action=repository_action_common_download&item_id=1658&item_no=1&attribute_id=22&file_no=2

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