报纸农疗相关文章的语义网络分析

Q3 Social Sciences
Yumin Park, Yong-Wook Shin
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引用次数: 0

摘要

背景和目标:尽管新冠肺炎大流行增加了对心理健康服务的需求,但获得服务的机会有限,导致服务缺口和离职。农业康复有望成功地用于促进个人和社区的心理健康,这可能是一个解决方案。这项研究旨在通过分析过去十年网络新闻文章的大数据趋势,为振兴与农业愈合相关的政策和研究提供基础数据。方法:从2012年1月1日至2021年12月31日,通过抓取Naver news,共收集2310篇与农业愈合相关的新闻文章。为了提取具有实际意义的名词,采用了Python 3.9中KoNLPy模块的Okt形态分析。语义网络分析验证了度中心性、介数中心性和特征向量中心性,以了解重要关键词的中心性和连通性。通过执行CONCOR分析以生成聚类,使用Gephi 0.9.2对数据进行可视化。结果:中心度最高的关键词是农业康复,其次是康复、护理农场、活力、RDA、公民和乡村旅游。农业治疗、康复、压力、城市、残疾、护理农场、痴呆症和农村地区的介数中心性最高。特征向量中心性在农业愈合中最高,其次是活力、愈合、护理农场和效果。作为CONCOR分析的结果,确定了四个集群:“农业愈合特征”、“农业愈合资源”、“农村愈合活动”和“农业愈合目标和效果”。结论:根据研究结果,社会对农业愈合改善公共健康的期望和需要成为话语的重要组成部分。这项研究有望帮助确定未来的研究和政策方向,因为农业康复的活力将继续提供国家福利服务,并寻求农业和农村地区的可持续增长。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semantic Network Analysis of Newspaper Articles related to Agro-healing
Background and objective: Despite the fact that the COVID-19 pandemic has increased the demand for mental health services, access has been limited, resulting in service gaps and severance. Agro-healing, which is expected to be utilized successfully to promote mental health for both individuals and communities, could be a solution. This study was conducted to provide basic data for revitalizing policies and research related to agro-healing by analyzing the trends in big data of online news articles over the last decade.Methods: A total of 2,310 news articles related to agro-healing were collected from January 1, 2012 to December 31, 2021 by crawling Naver News. To extract nouns with practical meaning, the Okt morphological analysis of the KoNLPy module in Python 3.9 was employed. Semantic network analysis was conducted to validate degree centrality, betweenness centrality, and eigenvector centrality in order to understand the centrality and connectivity of significant keywords. The data was visualized using Gephi 0.9.2 by performing CONCOR analysis to generate clusters.Results: The keywords with the highest degree centrality were agro-healing, followed by healing, care farm, vitality, RDA, citizens, and rural tourism. Agro-healing, Healing, stress, urban, disabilities, care farm, dementia, and rural area were highest in terms of betweenness centrality. The eigenvector centrality was highest in agro-healing, followed by vitality, healing, care farm, and effect. As a result of the CONCOR analysis, four clusters were identified: ‘agro-healing characteristics’, ‘agro-healing resources’, ‘agro-healing activities’, and ‘agro-healing target and effect’.Conclusion: According to the findings, social expectations and need for agro-healing to improve public health became a significant part of the discourses. This research is expected to help determine future research and policy directions, as the vitality of agro-healing continues to provide national welfare services and seek sustainable growth in agricultural and rural areas.
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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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