6533b872fe1ef96bd12d37c4
RESEARCH PRODUCT
false
subject
CheiRank0303 health sciencesInformation retrievalGeneral Computer ScienceGoogle matrixComputer sciencebusiness.industryGeneral Engineering01 natural sciences3. Good healthlaw.invention03 medical and health sciencesPageRanklaw0103 physical sciencesGlobal networkEncyclopediaGeneral Materials ScienceThe Internet010306 general physicsbusiness030304 developmental biologyNetwork analysisdescription
We consider the network of 5 416 537 articles of English Wikipedia extracted in 2017. Using the recent reduced Google matrix (REGOMAX) method we construct the reduced network of 230 articles (nodes) of infectious diseases and 195 articles of world countries. This method generates the reduced directed network between all 425 nodes taking into account all direct and indirect links with pathways via the huge global network. PageRank and CheiRank algorithms are used to determine the most influential diseases with the top PageRank diseases being Tuberculosis, HIV/AIDS, and Malaria. From the reduced Google matrix, we determine the sensitivity of world countries to specific diseases integrating their influence over all their history including the times of ancient Egyptian mummies. The obtained results are compared with the World Health Organization (WHO) data demonstrating that the Wikipedia network analysis provides reliable results with up to about 80 percent overlap between WHO and REGOMAX analyses.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-01-01 | IEEE Access |