TY - JOUR
KW - Collaborative Research Analysis
KW - Influence Analysis
KW - Network Centrality
KW - Quality of Reseach
KW - Statistical Analysis
AU - Sidra Razzaq
AU - Ahmad Kamran Malik
AU - Basit Raza
AU - Hasan Ali Khattak
AU - Giomar W. Moscoso Zegarra
AU - Yvan Díaz Zelada
AB - 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.
IS - Special Issue on Artificial Intelligence in Economics, Finance and Business
M1 - 3
N2 - 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.
PY - 2022
SP - 103
EP - 116
T2 - International Journal of Interactive Multimedia and Artificial Intelligence
TI - Research Collaboration Influence Analysis Using Dynamic Co-authorship and Citation Networks
UR - https://www.ijimai.org/journal/sites/default/files/2022-03/ijimai7_3_10_0.pdf
VL - 7
SN - 1989-1660
ER -