# Influence Flowers of Academic Entities

## TL;DR

The paper introduces the Influence Flower, a visual metaphor and interactive tool for exploring influence patterns among academic entities using a large citation dataset, enabling detailed influence analysis and comparison over time.

## Contribution

It presents the Influence Flower, a novel ego-centric visualization method for influence profiles, and an interactive web app for analyzing academic influence flows and their temporal changes.

## Key findings

- Supports analysis of researchers' career trajectories
- Enables examination of influence in interdisciplinary contexts
- Allows comparison of influence patterns over time

## Abstract

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 212million authors, their 176 million publications, and 1.2 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 interdisciplinary 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.