User:Multipotentialmike

Active Wikipedian with interests in many places 🤓

Some rudimentary data science from the WikiRank project:

We can draw a map of UN member states and their log10 PageRank centrality:



Notice, though, that it appears to correlate with overall economic size. Plotting GDP (nominal) against -log10 PageRank centrality:



It makes sense, then, to adjust for the size of the country's economy using the logarithmic interpolation, using the formula: $$\frac{-log_{10}{\text{observed PR centrality}}}{-\text{expected log10 PR centrality}}$$

This gives the adjusted map:



The ten highest states are:

We may also look at individual projects, using the data of the WP 1.0 bot and article quality/importance rankings. Here are three graphs from WikiProject Mathematics (captions are self-explanatory):



We can apply a similar technique to adjusting the PageRank vs quality data as we did to the countries' data, to produce a sort of 'neglect ratio', i.e. to identify those articles with much lower quality, as ranked 1 (Stub) to 8 (FA), than would be expected given their centrality. The 100 articles thus in most need of our attention are: