H-Index Analysis of Research Paper Using Web Crawling Techniques

EasyChair Preprint 11578

Abstract

The evaluation of research impact is a crucial aspect of academic research. In recent years, the h-index has become a widely used metric for assessing research productivity and impact. In this paper, we shall explore the use of web crawling techniques and Python programming language to collect publication data from Google Scholar and calculate the h-index of academic researchers. We 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. This paper presents a valuable contribution to the academic research community by providing an objective and efficient method for evaluating research impact.

Keyphrases: Google Scholar Metrics, Python, h-index, research impact, web crawling

@booklet{EasyChair:11578,
  author    = {Omprakash Kambli and Aarti Karande and Harshil Kanakia},
  title     = {H-Index Analysis of Research Paper Using Web Crawling Techniques},
  howpublished = {EasyChair Preprint 11578},
  year      = {EasyChair, 2023}}