Recruitment Boosted Epidemiological Model for Qualitative Study of Scholastic Influence Network

Journal of Scientometric Research,2021,10,1,110-118.
Published:May 2021
Author(s) affiliations:

Sudeepa Roy Dey1,*, Snehanshu Saha2, Rahul Reddy Nandyala3

1PES University, Visvesvaraya Technological University, Belagavi, Karnataka, INDIA.

2CS&IS and Anuradha and Prashanth Palakurthi Centre for Artificial Intelligence Research (APPCAIR), BITS PILANI KK Birla Goa Campus, Goa, INDIA.

3PESIT-Bangalore South Campus, Electronic City, Bengaluru, Karnataka, INDIA.


Measuring the true influence of a researcher over the past few years has been an important problem in field of scientometrics as it not only facilitates funding organizations, academic departments, and researchers but also indicates the impact of scholarly influence. The existing author level ranking metrics such as h-index, measures of citation counts, can ignore much of the nuance and are also often criticised for being unfair owing to its purely quantitative approach. In this paper we propose an influence diffusion model based on the Epidemiological model variant called as Recruitment boosted SEIR. Our model tries to simulate the spread of infection with the growth of influence of a researcher by remodeling various existing parameters and building a new concept for qualitative study of prolific authors. Finally, the reproduction number is derived, and the scores are computed. To validate our influence diffusion model, we perform experiments on the real author dataset collected from web of science and compare the researchers influence with their paper’s citation counts and h-index. Finally, we analyses the patterns about how researchers’ influence ranking increased over time. Our studies also show the various changing patterns of researchers between different h-index.

Data Flow and steps

Cite This Article

Vancouver Style ::

Cite this Article

Dey SRoy, Saha S, Nandyala RReddy. Recruitment Boosted Epidemiological Model for Qualitative Study of Scholastic Influence Network. Journal of Scientometric Research. 2021;10(1):110-118. doi:10.5530/jscires.10.1.13.