H-Index Analysis of Research Paper Using Web Crawling Techniques

The evaluation of research impact of publications is a crucial aspect of academic research. In the recent years, h-index has become a widely used metric for assessing research productivity and impact. In this paper, we shall explore the use of various web crawling techniques and Python programming language to collect publication data from Google Scholar and calculate the h-index of academic researchers. We would also demonstrate how the Scholarly package in Python can be used to retrieve publication data and perform h-index calculations, providing an efficient and objective means of evaluating research impact. Our proposed methodology combines the power of web crawling, h-index, and Python to enable comprehensive research analysis and evaluation. The Workflow for various steps of the process have been listed along with their individual steps and the corresponding code which implements the said functionality. Web crawling stands as an integral part of this process since the data is fetched from sources such as google scholar. The data used for analysis has been collected using the code snippets provided. This paper presents a valuable contribution to the academic research community by providing an objective and efficient method for evaluating research impact.