Keyword Analysis of Arboretums and Botanical Gardens Using Social Big Data

Abstract

This study collects social big data used in various fields in the past 9 years and explains the patterns of major keywords of the arboretums and botanical gardens to use as the basic data to establish operational strategies for future arboretums and botanical gardens. A total of 6,245,278 cases of data were collected: 4,250,583 from blogs (68.1%), 1,843,677 from online cafes (29.5%), and 151,018 from knowledge search engine (2.4%). As a result of refining valid data, 1,223,162 cases were selected for analysis. We came up with keywords through big data, and used big data program Textom to derive keywords of arboretums and botanical gardens using text mining analysis. As a result, we identified keywords such as 'travel', 'picnic', 'children', 'festival', 'experience', 'Garden of Morning Calm', 'program', 'recreation forest', 'healing', and 'museum'. As a result of keyword analysis, we found that keywords such as 'healing', 'tree', 'experience', 'garden', and 'Garden of Morning Calm' received high public interest. We conducted word cloud analysis by extracting keywords with high frequency in total 6,245,278 titles on social media. The results showed that arboretums and botanical gardens were perceived as spaces for relaxation and leisure such as 'travel', 'picnic' and 'recreation', and that people had high interest in educational aspects with keywords such as 'experience' and 'field trip'. The demand for rest and leisure space, education, and things to see and enjoy in arboretums and botanical gardens increased than in the past. Therefore, there must be differentiation and specialization strategies such as plant collection strategies, exhibition planning and programs in establishing future operation strategies.

Changes in the Cultural Trend of Use by Type of Green Infrastructure Before and After COVID-19 Using Blog Text Mining in Seoul

“…Choo (2020) identified the trends in consumption markets with focus on keywords related to 'solitary consumption', and Kim and Han (2019) analyzed the leisure trend using a semantic network. Previous studies conducted quantitative and focused analysis through keyword frequency analysis (Park and Bae, 2018;Park and Oh, 2019;Park and Yeon, 2020;Shin et al, 2020;Woo and Suh, 2021), and supplemented qualitative and auxiliary analysis through related keyword analysis. Recently, studies are conducted using quantitative and qualitative analysis through topic modeling Park et al, 2021).…”

“…Text mining studies had been used to identify massive research trends (Park and Bae, 2018 ;Byeon and Seo, 2020;Park et al, 2021;Choi and Choi., 2021) but recently they are actively conducted to identify the trends through perception changes and issues based on user experience (Kim, 2015;Kim and Jeon, 2018;Chae et al, 2021;Woo and Suh, 2018;Kong and Wang. 2019;Park and Oh, 2019;Do et al, 2020;Park and Yeon, 2020;Shin et al, 2020;Woo and Suh, 2020;Woo and Suh, 2021). Therefore, this study examines the changes in the main keywords of each type of green infrastructure before and after COVID-19 through blog text mining, derives key topics related to 'coronavirus', and analyzes related keywords, thereby capturing the changes in the cultural trend of use and providing policy implications.…”

The Effect of Social Media Content Types on User Reactions: Focused on a Case Study of Kew Gardens

“…Looking at the research trends related to Instagram data, Kim et al (2019) utilized Instagram's big data to determine the potential and importance of Instagram as a new tool in the field of regional survey and analysis as well as a data source from the perspective of urban users. Shin et al (2020) analyzed the original news text with a data mining technique using big data to understand how the public's interest in arboretums and botanical gardens has changed socially, economically, and culturally according to the trend of the times. Seo et al (2020) investigated how information about the Seoul Botanic Park is shared and propagated on the online system, and how recipients of such information perceive it, and reported that spatial information online is delivered in various types of text through social networking services (SNS) that enable users to communicate, rather than unilaterally through the official website.…”

Analysis on Cognitive Changes of Gardens between 2014 and 2018 by Big Data of Naver Channel

“…Big data 1) analytics 1) Big data does not merely indicate data that is big in size, but actually is used in various fields, which is a suitable method to analyze consumer perceptions, trends, and market flows . Kim (2016) reviewed the public perception and awareness of forest healing with SNS big data, and Shin et al (2020) used big data to identify how the social, economic, and cultural perceptions of citizens change over time, with keywords such as arboretums and botanical gardens. As for big data analytics or perception analysis related to gardens, Jang (2014) limited the scope of perception analysis to Suncheonman International Garden Expo, the search scope to blogs, and the period to the duration in which the expo was held, and then came up with implications by identifying visitor preferences and perception on certain gardens and spaces.…”