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

Q3 Social Sciences
Sung-Ho Kil, Hyesong Park, Eunseok Lee, Jin-Young Kim, Ji-Woo Kim
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引用次数: 0

Abstract

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.
基于文本挖掘的智能农场研究趋势与公众认知分析
背景和目标:为了应对气候变化、农村老龄化、粮食安全和第四次工业革命等近期问题,人们对能够利用信息和通信技术高效生产粮食的智能农场越来越感兴趣。为了应对国际问题,本研究通过文本挖掘分析了国际期刊、KCI期刊以及Instagram标签上发表的关于智能农场的文章,并确定了相关的研究趋势和公众意识。方法:本研究收集了2010年至2021年关于智能农场的584篇文章和2021年上传的Instagram帖子中的标签。为了提高分析结果的可靠性,只从摘要和标签中提取名词,并通过删除习惯出现的名词和组合同义词来进行数据预处理。然后,我们分析了频率、度中心性、介数中心性和主题建模。结果:研究数据对高频词和中心词的分析结果如下。KCI和国际期刊文章倾向于主要关注智能农场高效运营的ICT系统开发。然而,KCI的文章考虑了建立这些技术的相关政策。另一方面,国际期刊文章倾向于在比KCI文章更广泛的农业领域对智能农场进行研究。Instagram上的主要话题是减肥食品、农村移民和城市农业。这一结果表明,通过智能农场提供的健康食品、体验和教育正在引起公众的兴趣。结论:目前,对智能农场的研究趋势分析不足。有鉴于此,这项研究具有重要意义,因为它通过考虑研究文章和Instagram帖子,纳入了学术趋势和公众意识。我们预计这项研究的结果将被用作决策的有用数据,以确定未来推进智能农场所需的研究和政策方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of People, Plants, and Environment
Journal of People, Plants, and Environment Social Sciences-Urban Studies
CiteScore
1.10
自引率
0.00%
发文量
42
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