Exploring Differences in Academic Influence of Countries Based on Algorithm Development——A Case Study of Algorithms in the Field of Natural Language Processing
With the development of digital technology,algorithms have become increasingly important in various fields,but few papers have examined the performance of different countries in their algorithm development efforts.Taking the field of Natural Language Processing as an example,this article uses machine learning methods to extract the algorithms mentioned in the academic papers and obtain the complete set of algorithms.It collects the proposed countries and related information of all algorithms,and analyzes the academic influence of different countries in terms of algorithms,both quantitatively and qualitatively.The results show that there are obvious differences between countries given the number of algorithms,and that China and the United States are the main force in proposing algorithms;as for the quality of algorithms,the United States performs well in terms of comprehensive citations,the gap between the average citations of each country is small,and the rankings of Australia and the Ukraine are improved significantly.Taking into account the number and quality of algorithms,the academic influence of different countries can be divided into four types,from which exemplary countries with superior quantitative and qualitative performance can be identified,as well as potential countries with high influence in a single dimension.This paper provides a new perspective for evaluating the academic influence of countries,institutions,and individuals,and verifies the possibility of using fine-grained knowledge to evaluate a country's academic influence,which provides a reference for the academic cooperation between countries in the process of algorithmic innovation.
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