Identifying Local Characteristics for Customized Policy Application Within Rural Areas Using LDA Topic Modelling

Hogyeong Jeong, Yeeun Shin, Sang-woo Lee, Seokjun Han and Kyungjin An ()
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Hogyeong Jeong: Department of Forestry and Landscape Architecture, Graduate School, Konkuk University, Seoul 05029, Republic of Korea
Yeeun Shin: Laboratory of Spatial Design Research, Konkuk University, Seoul 05029, Republic of Korea
Sang-woo Lee: Department of Forestry and Landscape Architecture, Graduate School, Konkuk University, Seoul 05029, Republic of Korea
Seokjun Han: HIGHDATA, Seoul 05836, Republic of Korea
Kyungjin An: Department of Forestry and Landscape Architecture, Graduate School, Konkuk University, Seoul 05029, Republic of Korea

Sustainability, 2025, vol. 17, issue 12, 1-18

Abstract: Rural plans incorporating regional identity are vital for fostering regional revitalization and offering viable policy alternatives. The need for a systematic approach that recognizes both the diversity and shared characteristics of rural areas has become increasingly clear. Although numerous studies have explored rural classification, research examining specific regional characteristics remains limited. Hence, this study aimed to establish a comprehensive standard for developing effective rural plans. To this end, a study was conducted to classify the characteristics of rural areas using topic modeling, which is a text-mining algorithm. An analysis of publications on rural revitalization projects in Korea over the past decade revealed five common factors of success themes across each region. The five success factors, “local cultural experience”, “environment and landscape utilization”, “community activation”, “regional infrastructure development”, and “local economic activation”, should be considered in rural areas with different characteristics when establishing rural plans and policies. This classification of success factors serves as the foundation for establishing rural plans and policies. By applying different weights to the five success factors according to the unique characteristics and conditions of each region, it would open a great number of possibilities to establish more precise and effective customized plans. Future research is required to provide more empirical and broadly applicable results based on the classification framework proposed in this study.

Keywords: rural plans; regional identity; text mining; topic modeling; classification; depopulation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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