TY - GEN
T1 - Influence Flowers of Academic Entities
AU - Shin, Minjeong
AU - Soen, Alexander
AU - Readshaw, Benjamin T.
AU - Blackburn, Stephen M.
AU - Whitelaw, Mitchell
AU - Xie, Lexing
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - 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 212 million 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.
AB - 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 212 million 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.
KW - Empirical studies in visualization
KW - Human-centered computing
KW - Visual analytics
KW - Visualisation application domains
KW - Visualization
KW - Visualization systems and tools
UR - https://www.scopus.com/pages/publications/85081059122
U2 - 10.1109/VAST47406.2019.8986934
DO - 10.1109/VAST47406.2019.8986934
M3 - Conference Paper
T3 - 2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings
BT - 2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings
A2 - Chang, Remco
A2 - Keim, Daniel
A2 - Maciejewski, Ross
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th IEEE Conference on Visual Analytics Science and Technology, VAST 2019
Y2 - 20 October 2019 through 25 October 2019
ER -