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

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: Cobb Douglas model, Data acquisition methods, data visualization, Graph database, Neo4j, Web scraping.