Using the English Wikipedia network of more than 5 million articles we analyze interactions and interlinks between the 34 largest pharmaceutical companies, 195 world countries, 47 rare renal diseases and 37 types of cancer. The recently developed algorithm of reduced Google matrix (REGOMAX) allows us to take into account direct Markov transitions between these articles but also all indirect ones generated by the pathways between these articles via the global Wikipedia network. Thus this approach provides a compact description of interactions between these articles that allows us to determine the friendship networks between articles, the PageRank sensitivity of countries to pharmaceutical companies and rare renal diseases. We also show that the top pharmaceutical companies of Wikipedia PageRank are not those of the top list of market capitalization.
computer science, artificial intelligence
(engineering science), computer science, information systems
(engineering science), genetics & heredity
(fundamental biology), health care sciences & services
(medical research), oncology
(medical research), pharmacology & pharmacy
(medical research), public, environmental & occupational health
(medical research, social sciences), physics, mathematical
(physics), multidisciplinary sciences
Data acquisition : from 1 May 2017 to 31 May 2017
Data provision : 20 Apr 2019
Metadata record :
Creation : 12 Aug 2019
General, Research, Stakeholder, Policy maker, Informal Education
Formats : application/pdf, image/png, image/svg+xml, image/x-eps, text/csv, text/html, text/plain
Data acquisition methods :
- Derived or compiled data :
Web crawling of Wikipedia editions (May 2017) to retrieve information.
- Simulation or computational data :
PageRank, CheiRank and 2DRank algorithms have been used to rank articles of the English Wikipedia language edition (May 2017).
Reduced Google matrix method has been used to infer interactions between articles.