Influence Flowers of Academic Entities

Minjeong Shin, Alexander Soen, Benjamin T. Readshaw, Stephen M. Blackburn, Mitchell Whitelaw, Lexing Xie
Australian National University

We present the Influence Flower, a new visual metaphor for the influence profile of academic entities, including people, projects, institutions, conferences, and journals. While many tools quantify influence, we aim to expose the flow of influence between entities. The Influence Flower is an ego-centric graph, with a query entity placed in the centre. The petals are styled to reflect the strength of influence to and from other entities of the same or different type. For example, one can break down the incoming and outgoing influences of a research lab by research topics. The Influence Flower uses a recent snapshot of Microsoft Academic Graph, consisting of 200+ million authors, their publications, and 1+ billion citations. An interactive web app, Influence Map, is constructed around this central metaphor for searching and curating visualisations. We also propose a visual comparison method that highlights change in influence patterns over time. We demonstrate through several case studies that the Influence Flower supports data-driven inquiries about the following: researchers’ careers over time; paper(s) and projects, including those with delayed recognition; the interdiciplinary profile of a research institution; and the shifting topical trends in conferences. We also use this tool on influence data beyond academic citations, by contrasting the academic and twitter activities of a researcher.

Published in the IEEE Conference on Visual Analytics Science & Technology (VAST), 2019

Paper BibTex
title={Influence Flowers of Academic Entities},
author={Shin, Minjeong and Soen, Alexander and Readshaw, Benjamin T and Blackburn, Stephen M and Whitelaw, Mitchell and Xie, Lexing},
booktitle={The {IEEE} Conference on Visual Analytics Science and Technology (VAST)},

* Go to the Influence Map website:

* Github Repository:

* Demo videos:

The influencemap project is supported by ANU College of Engineering and Computer Science, and ACM SIGMM. We thank Microsoft for sharing the Academic Graph data, and NECTAR for providing computing infrastructure.