Interactions of pharmaceutical companies with world countries, cancers and rare diseases from Wikipedia network analysis

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.

本研究依托拥有超500万条目的英文维基百科（Wikipedia）网络，对34家全球顶级制药企业、195个主权国家、47种罕见肾脏疾病以及37类癌症之间的交互关系与条目间交叉链接展开分析。我们借助新近提出的约简谷歌矩阵（reduced Google matrix, REGOMAX）算法，不仅能够考量上述条目间的直接马尔可夫转移关系，还可纳入经由全球维基百科网络形成的条目间通路所产生的全部间接关联。该方法可对这些条目间的交互关系实现简洁刻画，借此得以确定条目间的关联网络、各国针对制药企业与罕见肾脏疾病的佩奇排名（PageRank）敏感度。本研究同时证实，维基百科佩奇排名靠前的制药企业，与市值榜单前列的制药企业并不重合。