Analysis of the Wikipedia network of mathematicians
File(s)1902.07622v2.pdf (1.29 MB)
Working paper
Author(s)
Chen, Bingsheng
Lin, Zhengyu
Evans, Tim S
Type
Working Paper
Abstract
We look at the network of mathematicians defined by the hyperlinks between
their biographies on Wikipedia. We show how to extract this information using
three snapshots of the Wikipedia data, taken in 2013, 2017 and 2018. We
illustrate how such Wikipedia data can be used by performing a centrality
analysis. These measures show that Hilbert and Newton are the most important
mathematicians. We use our example to illustrate the strengths and weakness of
centrality measures and to show how to provide estimates of the robustness of
centrality measurements. In part, we do this by comparison to results from two
other sources: an earlier study of biographies on the MacTutor website and a
small informal survey of the opinion of mathematics and physics students at
Imperial College London.
their biographies on Wikipedia. We show how to extract this information using
three snapshots of the Wikipedia data, taken in 2013, 2017 and 2018. We
illustrate how such Wikipedia data can be used by performing a centrality
analysis. These measures show that Hilbert and Newton are the most important
mathematicians. We use our example to illustrate the strengths and weakness of
centrality measures and to show how to provide estimates of the robustness of
centrality measurements. In part, we do this by comparison to results from two
other sources: an earlier study of biographies on the MacTutor website and a
small informal survey of the opinion of mathematics and physics students at
Imperial College London.
Date Issued
2019-02-21
Citation
2019
Publisher
arXiv
Copyright Statement
© 2019 The Author(s)
Identifier
http://arxiv.org/abs/1902.07622v2
Subjects
cs.DL
cs.DL
cs.SI
physics.soc-ph
Notes
(Updated two captions in the appendix)
Publication Status
Published