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This study selects the literature metadata included in the Semantic School. The database uses natural language processing technology to obtain the key points in the paper. Through semantic analysis, the research topic of the paper is divided into 19 disciplines, and the author of the document is disambiguated. The metadata in the data set is crawled randomly, and the time range is set from 1990 to 2015. Since the number of published papers is an important outcome variable to measure the level of individual academic influence, researchers with too few published papers may have just started or are not full-time engaged in academic research, and are not suitable for use as the research sample of this article, so researchers with more than 5 published papers are set as the research object. At the same time, individuals with missing values in the discipline to which the scholars belong are excluded. Finally, there were 69759 eligible scholars, 528186 papers and 18849075 citations.
37 views reported since publication in 2023.