Journal of Scientometric Research logo
Submit
Journal of Scientometric ResearchACADEMIC PUBLISHING
Communication

Genealogy Tree: Understanding Academic Lineage of Authors via Algorithmic and Visual Analysis

1, 1, 1★, 1, 1★ Corresponding author

  1. 1Department of Computer Science and Engineering, PESIT Bangalore South Campus, Bangalore, Karnataka, INDIA.

CORRESPONDENCE

Sudeepa Roy Dey

Department of Computer Science and Engineering, PESIT Bangalore South Campus, Bangalore, Karnataka, INDIA.

sudeepar@pes.edu

Received: 02-03-2018; Revised: 17-07-2018; Accepted: 21-08-2018.

Volume 7, Issue 2 · pp. 120-124 · 2018 · DOI: 10.5530/jscires.7.2.18

ABSTRACT

Ancestry and Genealogy tree are proven tools to determine the lineage of any person and establish dependencies among individuals. Genealogy tree can be exploited further to gain information about the researcher and his scholastic lineage which is of paramount importance in today’s world of computer technology. This insight into academic genealogy could be ways of helping PhD students achieve academic socialization within the discipline, by making explicit connections that may be influential. Awareness of his scientific heritage, gives the user a broader perspective of his own research project. This paper also highlights and investigates how this academic network is exploited by certain researchers using various visualization tools. It was observed during this work that the credibility and influence factor is determined by the various citations obtained by an author and to improve their rankings in various forums, they tend to collaborate in their academic circle and boost their citation count. A recent trend among researchers is to form communities based on their academic relationships and rely on copious citations for their mutual benefit. Tracing the genealogical relationships can be helpful in detecting such communities and also create a more quality aware metrics using a lineage independent model for computation of author level metrics.

KEYWORDS

Open in new tab

REFERENCES

As published

Showing references and in-text citations exactly as published.

    Cite this article

    SELECT FORMAT

    Anil, S., Kurian, A., Dey, S. R., Saha, S., & Sinha, A. (2018). Genealogy Tree: Understanding Academic Lineage of Authors via Algorithmic and Visual Analysis. Journal of Scientometric Research, 7(2), 120-124. https://doi.org/10.5530/jscires.7.2.18

    Copyright and licence

    © 2018 Author(s)

    This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms. CC BY-NC-SA 4.0