Novel Weighted Citation Methods for Ranking Academic Authors: Introducing NWC and TSWC Indexing Methods
Year: 2025
Type: article
Abstract: Author ranking is an essential metric for assessing academic performance and facilitating comparisons within citation networks. While several indexing methods have been proposed to enhance author ranking, existing approaches often fail to capture the true contribution of authors to the literature. This study introduces two novel weighted citation methods to improve author ranking in academic citation networks. The first method, Normalized Weighted Citations (NWC), evaluates the rankings of co-authors within a publication. The second method, Topic-Sensitive Weighted Citations (TSWC), assigns scores to authors based on their relevance to specific research domains. Our goal is to identify both highly influential and less prominent authors within citation networks on a global scale. We evaluate our methods using scholarly publication datasets and compare them with a baseline approach. Experimental results demonstrate that the proposed methods outperform traditional ranking techniques, highlighting the importance of accurately assessing researchers’ impact in citation networks.
DOI: 10.33317/ssurj.658
Authors: Mujeeb Ur Rehman, Akbar Hussain, Imtiaz Hussain, Usman Sardar, Muhammad Hasnain
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4411845126