Bibliometric analysis of the published literature on machine learning in economics and econometrics
An extensive literature providing information on published materials in machine learning exists. However, machine learning is still a rather new concept in the fields of economics and econometrics. This study aims to identify different properties of published documents about machine learning in econ...
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| Veröffentlicht in: | Social network analysis and mining 2022-12, Vol.12 (1), p.109-109, Article 109 |
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| creator | Çağlayan Akay, Ebru Yılmaz Soydan, Naciye Tuba Kocarık Gacar, Burcu |
| description | An extensive literature providing information on published materials in machine learning exists. However, machine learning is still a rather new concept in the fields of economics and econometrics. This study aims to identify different properties of published documents about machine learning in economics and econometrics and therefore to draw a detailed picture of recent publications from bibliometric analysis perspectives. For the aim of the study, the data are collected from the publications indexed by Web of Science and Scopus databases from the period 1991 to 2020. Inthe study, the data have been illustrated by VOSviewer for science mapping. The analysis of variance has also been used to identify the links between the number of citations of articles and years. The findings obtained provides information about the studies on machine learning in the relevant field conducted in the past, as well as providing an opportunity to gain knowledge about the researched area by shedding light on what the future research areas would be. There is no doubt that it attracts attention has increased significantly on machine learning in the field of economics and econometrics and academic publications on machine learning in the relevant field have increased over the last decade. |
| doi_str_mv | 10.1007/s13278-022-00916-6 |
| format | Article |
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Netw. Anal. Min</addtitle><description>An extensive literature providing information on published materials in machine learning exists. However, machine learning is still a rather new concept in the fields of economics and econometrics. This study aims to identify different properties of published documents about machine learning in economics and econometrics and therefore to draw a detailed picture of recent publications from bibliometric analysis perspectives. For the aim of the study, the data are collected from the publications indexed by Web of Science and Scopus databases from the period 1991 to 2020. Inthe study, the data have been illustrated by VOSviewer for science mapping. The analysis of variance has also been used to identify the links between the number of citations of articles and years. The findings obtained provides information about the studies on machine learning in the relevant field conducted in the past, as well as providing an opportunity to gain knowledge about the researched area by shedding light on what the future research areas would be. There is no doubt that it attracts attention has increased significantly on machine learning in the field of economics and econometrics and academic publications on machine learning in the relevant field have increased over the last decade.</description><subject>Algorithms</subject><subject>Applications of Graph Theory and Complex Networks</subject><subject>Artificial intelligence</subject><subject>Bibliographic coupling</subject><subject>Bibliometrics</subject><subject>Big Data</subject><subject>Citations</subject><subject>Collaboration</subject><subject>Computer Science</subject><subject>Data Mining and Knowledge Discovery</subject><subject>Documents</subject><subject>Econometrics</subject><subject>Economic analysis</subject><subject>Economics</subject><subject>Game Theory</subject><subject>Humanities</subject><subject>Law</subject><subject>Machine learning</subject><subject>Mapping</subject><subject>Methodology of the Social Sciences</subject><subject>Original</subject><subject>Original Article</subject><subject>Social and Behav. 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| subjects | Algorithms Applications of Graph Theory and Complex Networks Artificial intelligence Bibliographic coupling Bibliometrics Big Data Citations Collaboration Computer Science Data Mining and Knowledge Discovery Documents Econometrics Economic analysis Economics Game Theory Humanities Law Machine learning Mapping Methodology of the Social Sciences Original Original Article Social and Behav. Sciences Social networks Statistics for Social Sciences Variance analysis |
| title | Bibliometric analysis of the published literature on machine learning in economics and econometrics |
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