The Influence Map project maps the flow of intellectual influence for academic entities.


The main visual metaphor is the influence flower, created around a center entity with its publications:
  • Blue archs denote incoming influence, and is proportional to the number of references made.
  • Red archs denote outgoing influence, and is proportional to the number of citations recieved.
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Dataset


176 million
Publications

1.2 billion
Citations

212 million
Authors

52 thousand
Venues

25 thousand
Institutions
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 2018-06-29, 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 strenth of this relation is reflected in the thickness of the edge.
  • The red edges denotes the influence the center has towards the outer entities, i.e., an outer entity citing a paper by the center. The blue edges denotes the influence the outer entities have towards the center, i.e., the center cites a paper by an outer entities.
  • The color of the outer nodes denote the difference between incoming and outgoing influence score. A blue node indicates that the associated entity has influence 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,
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

Alexander Soen
Benjamin Readshaw
Minjeong Shin
Lexing Xie
Stephen Blackburn

About the project

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