BIBLIOMETRIC ANALYSIS OF INVESTMENT CLASSIFICATION CRITERIA

I. Croitoru, N. Ignat, Paula Paraschiva Spiridon, Luciana Dragomir, Maria Valerica Șoloiu, Alexandra Bratiloveanu
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Abstract

"In this paper, the scientific articles from the Web of Science base were analyzed, which address the investment classification criteria by means of the bibliometric analysis. Querying the Web of Science database and applying filters revealed a sample of 273 articles. The distribution by years, by countries, by authors, by categories, by fields of research, by sustainable development goals of this sample was followed. Also, within the work, a qualitative analysis was carried out, following the words and phrases with the highest density in the studied articles. The investigation method was based on the PRISMA Statements methodology. To determine the correlations regarding the countries of origin of the authors, the Co-authorship filter was used with a minimum number of 10 documents/country and a minimum number of 11 citations/country, so out of 73 countries only 14 met the conditions for analysis. For the word density analysis, the co-occurrence filter was applied, with a minimum occurrence of 5, resulting in 37 words grouped into 5 clusters. To support the conclusions, the following classifications were analyzed: WOS Categories, Research Areas, Sustainable Development Goals, Citation Topics Micro. The results of the research constitute the starting point for future analyzes in the field of investments."
投资分类标准的文献计量分析
"本文分析了 Web of Science 数据库中的科学文章,这些文章通过文献计量学分析方法解决了投资分类标准问题。通过查询 "科学网 "数据库并应用筛选器,获得了 273 篇文章样本。对样本的年份、国家、作者、类别、研究领域和可持续发展目标进行了分析。此外,在这项工作中,还根据所研究文章中密度最高的单词和短语进行了定性分析。调查方法以 PRISMA 声明方法为基础。为了确定作者原籍国的相关性,使用了共同作者筛选器,要求每个国家至少有 10 篇文献,每个国家至少有 11 篇引文,因此在 73 个国家中,只有 14 个国家符合分析条件。在词密度分析中,使用了共现过滤器,最小出现次数为 5 次,结果有 37 个词被分成 5 个词组。为支持结论,对以下分类进行了分析:WOS 类别、研究领域、可持续发展目标、引文主题微型。研究结果是未来投资领域分析的起点"。
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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