  Visualization of the massive data is a challenging endeavor. Extracting data
and providing graphical representations can aid in its effective utilization in
terms of interpretation and knowledge discovery. Publishing research articles
has become a way of life for academicians. The scholarly publications can
shape-up the professional growth of authors and also expand the research and
technological growth of a country, continent and other demographic regions.
Scholarly articles have grown in gigantic numbers that are published in
different domains by various journals. Information related to articles,
authors, their affiliations, number of citations, country, publisher,
references and other information is like a gold mine for statisticians and data
analysts. This data when used skillfully, via visual analysis tool, can provide
valuable understanding and can aid in deeper exposition for researchers working
in domains like scientometrics and bibliometrics. Since the data is not readily
available, we used Google scholar, a comprehensive and free repository of
scholarly articles, as data source for our study. Data was scraped from Google
scholar and stored as a graph and later visualized in the form of nodes and its
relationships, which offered discerning and concealed information of growing
impact of articles, journals and authors in their domains. Not only this,
evident domain shift of an author, various research domains spread for an
author, predicting emerging domain and subdomains, detecting cartel behavior at
Journal and author-level was also depicted by graphical analysis. Neo4j graph
database was used in the background to help store the data in structured
manner.
