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 compare 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.
CITATION STYLE
Stephany, F., & Braesemann, F. (2017). An exploration of wikipedia data as a measure of regional knowledge distribution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10540 LNCS, pp. 31–40). Springer Verlag. https://doi.org/10.1007/978-3-319-67256-4_4
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