The Analysis of Research Trends and Public Awareness of Smart Farms using Text Mining

• 영문명: The Analysis of Research Trends and Public Awareness of Smart Farms using Text Mining
• 발행기관: 인간식물환경학회
• 저자명: Sung-Ho Kil Hye-Mi Park Eunseok Lee Jin-Young Kim Ji-Woo Kim
• 간행물 정보: 『인간식물환경학회지(JPPE)』제26권 제1호, 9~21쪽, 전체 13쪽
• 주제분류: 자연과학 > 자연과학일반
• 파일형태: PDF
• 발행일자: 2023.02.28

영문 초록

Background and objective: To deal with recent issues such as climate change, rural aging, food security, and the Fourth Industrial Revolution, there is a growing interest in smart farms that can efficiently produce food with ICT. In response to the international issues, this study analyzed articles on smart farms published in international journals and KCI journals as well as Instagram hashtags through text mining and identified relevant research trends and public awareness. Methods: This study collected total 584 articles on smart farms from 2010 to 2021 and hashtags in Instagram posts uploaded in 2021. To improve the reliability of the analysis results, nouns were exclusively extracted from the abstracts and hashtags, and data preprocessing was performed by removing nouns that appear customarily and combining synonyms. After that, we analyzed frequency, degree centrality, betweenness centrality, and topic modeling. Results: The analysis results of words with high frequency and centrality by research data are as follows. KCI and international journal articles had a tendency to mainly focus on ICT system development for efficient operation of smart farms. However, KCI articles considered relevant policies to establish the technologies. On the other hand, international journal articles tended to conduct research on smart farms in a wider area of agricultural fields than KCI articles. The main topics on Instagram were diet food, rural migration, and urban agriculture. This result shows that healthy food, experiences, and education through smart farms are gaining public interest. Conclusion: Currently, there is insufficient analysis of research trends in smart farms. In this vein, this study has significance as it included academic trends and public awareness by considering both research articles and Instagram posts. We expect the results of this study to be used as useful data for decision making to set the research and policy directions required to advance smart farms in the future.

목차

Introduction

Research Methods

Results and Discussion

Conclusion

References

키워드

big data algorithm semantic network analysis topic modeling plant