Abstract
This study conducted an analysis with the semantic network analysis technique to figure out house values sought after in the messages of local apartment sales advertisements. The study collected analysis data from the messages of 54 apartment sales advertisements in total published in B, which is one of the most representative newspapers in Busan and has the most subscribers, for two years of June 2020~June 2022. The analysis focus was put on the headlines, subheadlines, body copies, and captions of newspaper ads. R was used in a text mining analysis including the analysis of word clouds and semantic networks as well as frequency analysis to identify the housing value factors conveyed to consumers exposed to these advertising messages. The main findings were summarized as follows: first, such keywords as
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