Influence flower visualises citation influences among academic entities, including papers, authors, institutions, and research topics.

  • Blue arcs denote incoming influence, with their thickness proportional to the number of references made.
  • Red arcs denote outgoing influence, with their thickness proportional to the number of citations received.
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252 million

1.6 billion

262 million

54 thousand

26 thousand
Influence statistics are computed from Microsoft Academic Graph (MAG) dataset. MAG is the data source behind Microsoft Academic Search, indexing data about scientific publication records, citation relationships, as well as authors, institutions, journals, conferences, and fields of study. The current influencemap is based on a MAG graph snapshot from 2021-02-15, which will be regularly updated.

Computing influence scores

We compute influence as a function of paper citations.
Each of the edges of the graph signifies the flow of influence to and from the center node, the strength of this relation is reflected in the thickness of the edge.
  • The red edges denote the influence the center has towards the outer entities, i.e., an outer entity citing a paper by the center. The blue edges denote the influence the outer entities have towards the center, i.e., the center cites a paper by an outer entity.
  • The color of the outer nodes denotes the difference between incoming and outgoing influence scores. A blue node indicates that the associated entity has influenced the center more than the center has influenced itself. Likewise, a red node indicates the center has influenced the node's entity more than it has influenced the center.
We normalize the influence contribution by the number of authors in the cited paper, to prevent papers associated with a large number of entities from creating an overwhelming amount of influence. Check our paper for more information.
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.

ANU Computational Media Lab

Building 145, Science Rd
College of Engineering and Computer Science
The Australian National University
Canberra, ACT 2601, Australia

Our team

Minjeong Shin
Alexander Soen
Jakub Nabaglo
Benjamin Readshaw
Lexing Xie
Mitchell Whitelaw
Stephen Blackburn

About the project

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