Research Collaboration Influence Analysis Using Dynamic Co-authorship and Citation Networks.

Sidra Razzaq; Ahmad Kamran Malik; Basit Raza; Hasan Ali Khattak; Giomar W. Moscoso Zegarra; Yvan Díaz Zelada

doi:10.9781/ijimai.2022.03.001

Authors

Sidra Razzaq COMSATS University Islamabad
Ahmad Kamran Malik COMSATS University Islamabad
Basit Raza COMSATS University Islamabad
Hasan Ali Khattak National University of Sciences and Technology
Giomar W. Moscoso Zegarra Escuela de Posgrado Newman
Yvan Díaz Zelada Escuela de Posgrado Newman

DOI:

https://doi.org/10.9781/ijimai.2022.03.001

Keywords:

Collaborative Research Analysis, Influence Analysis, Network Centrality, Quality of Reseach, Statistical Analysis

Abstract

Collaborative research is increasing in terms of publications, skills, and formal interactions, which certainly makes it the hotspot in both academia and the industrial sector. Knowing the factors and behavior of dynamic collaboration network provides insights that helps in improving the researcher’s profile and coordinator’s productivity of research. Despite rapid developments in the research collaboration process with various outcomes, its validity is still difficult to address. Existing approaches have used bibliometric network analysis with different aspects to understand collaboration patterns that measure the quality of their corresponding relationships. At this point in time, we would like to investigate an efficient method to outline the credibility of findings in publication—author relations. In this research, we propose a new collaboration method to analyze the structure of research articles using four types of graphs for discerning authors’ influence. We apply different combinations of network relationships and bibliometric analysis on the G-index parameter to disclose their interrelated differences. Our model is designed to find the dynamic indicators of co-authored collaboration with an influence on the author’s behavior in terms of change in research area/interest. In the research we investigate the dynamic relations in an academic field using metadata of openly available articles and collaborating international authors in interrelated areas/domains. Based on filtered evidence of relationship networks and their statistical results, the research shows an increment in productivity and better influence over time.

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