从国际COVID-19出版物中发现基于国家的出版物的文本分类技术
Farshid Danesh1, Meisam Dastani2
1Information Management Department, ISC, Shiraz, Iran.
Digital health
|July 10, 2023
概括
这项研究使用文本挖掘来分析COVID-19出版物,发现伊朗和其他国家之间一致的研究趋势,特别是在疫苗和抗体主题上.
科学领域:
- 图书统计学 图书统计学
- 文本挖掘 (Text Mining) 是一个很好的方法.
- 医疗信息学 医疗信息学
背景情况:
- COVID-19研究的激增需要先进的分析方法.
- 了解全球和国家研究趋势对于有效的健康战略至关重要.
研究的目的:
- 在国际COVID-19研究中应用文本分类技术来识别基于国家的出版物.
- 分析伊朗和全球COVID-19出版物之间的研究主题的一致性.
主要方法:
- 应用研究使用文本挖掘技术,包括集群 (隐性迪里克莱特分配 - LDA) 和文本分类 (支持矢量机 - SVM).
- 在2019年11月至2021年6月期间,PubMed Central (PMC) 对COVID-19出版物的分析.
- 使用Python和scikit-learn库进行文本分类.
主要成果:
- 在国际和伊朗的COVID-19出版物中,使用LDA确定了七个不同的话题.
- 全球和国家最突出的研究领域是"COVID-19中的社会和技术" (分别是2021年4月和2021年2月).
- 2021年4月 (国际) 和2021年2月 (国内) 发生了出版率的峰值.
结论:
- 在伊朗和国际COVID-19出版物之间观察到一个共同的趋势和一致性.
- 具体而言",Covid-19蛋白质:疫苗和抗体反应"的主题显示了并行的研究和出版模式.
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