Preprint
An exploration of Wikipedia data as a measure of regional knowledge distribution
- Abstract:
- In today’s economies, knowledge is the key ingredient for prosperity. However, it is hard to measure this intangible asset appropriately. Standard economic models mostly rely on common measures such as enrollment rates and international test scores. However, these proxies focus rather on the quality of education of pupils than on the distribution of knowledge among the whole population, which is increasingly defined by alternative sources of education such as online learning platforms. As a consequence, the economically relevant stock of knowledge in a region is only roughly approximated. Furthermore, they are abstract in content, and both capital-, and time-consuming in census. This paper proposes to explore Wikipedia data as an alternative source of capturing the knowledge distribution on a narrow geographical scale. Wikipedia is by far the largest digital encyclopedia worldwide and provides data on usage and editing publicly. We com- pare Wikipedia usage worldwide and edits in the U. S. to existing measures of the acquisition and stock of knowledge. The results indicate that there is a significant correlation between Wikipedia interactions and knowledge approximations on different geographical scales. Considering these results, it seems promising to further explore Wikipedia data to develop a reliable, inexpensive, and real-time proxy of knowledge distribution around the world.
- Publication status:
- Published
- Peer review status:
- Not peer reviewed
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(Preview, Pre-print, pdf, 880.1KB, Terms of use)
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- Preprint server copy:
- 10.31235/osf.io/c2gd8
Authors
- Preprint server:
- OSF
- Publication date:
- 2019-10-09
- DOI:
- Server owner:
- Center for Open Science
- Language:
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English
- Keywords:
- Pubs id:
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1064091
- UUID:
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uuid_34746023-cf4a-477f-b814-79c75ad00dad
- Local pid:
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pubs:1064091
- Source identifiers:
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W3133704323
- Deposit date:
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2026-01-10
- ARK identifier:
Terms of use
- Copyright holder:
- Stephany and Braesemann
- Copyright date:
- 2019
- Rights statement:
- ©2019 The Authors. This paper is an open access article distributed under the terms of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)
- Licence:
- CC Attribution (CC BY)
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