『주택연구』의 30년간 연구경향: 텍스트 마이닝 접근법

Abstract

We analyze the research trend of the Housing Research Review over the period of 1993 to 2021. In particular, adopting text-mining methodologies: word frequency analysis, wordcloud technique, N-gram, and Topic Modeling, we analyze titles and keywords of all the papers on the journal. Based on those analyses, we find that words that the papers on the journal most frequently used over the past 30 years are ‘housing’ and ‘research’, which are followed by ‘price’, ‘househhold’ and ‘income’. Our word proximity analsyis shows the most-related keywords; housing prices, housing markets, fluctuations, and trading volume in terms of market and price structure; housing occupancy and household changes in terms of housing demand.
 Our analysis of Latent Dirichlet Allocation reveals six categories; ‘the ownership and apartments’, ‘price and space’, ‘real estate policy and regulation’, ‘household’s decision in housing market’, ‘regional characteristics evaluation’, and ‘residency and rental housing’. The most interested topics are related to ‘price’, and we confirm that the topics of interest has been changed over the decades; from ‘development and management’ and ‘rental housing and real estate’ to ‘public housing’. In addition, our analysis confirms that housing research on Housing Studies Review is comprehensive and includes a variety of housing topics.