The title says it already while a new r-blogger post helped tremendously to analyze my own scholar account for the first time.
I always wondered how Google Scholar ranked my 474 earlier co-authors.
The ranking above shows not the most relevant ones, in particular as there was a lot of name dropping of institute heads in the past. There are even people that I never met before and there are some co-authors that I don’t want to be associated with. But well, there are so many excellent people that I highly appreciate.
The published R script is very helpful for finding out more details. I had to adjust only two lines where I dropped the new column for interpolated rank. Also the dataset was not unique
# all_df$interrank <- na.approx(all_df$interrank) all_df <- distinct(all_df, coauthors, .keep_all = TRUE) %>% mutate(cites_corr = cites/n)
Dividing citations to the number of papers reversed the picture where suddenly the best co-authors moved up in the ranking.
BTW the original Google algorithm remains in the dark while the blog post finds
So the total co-citations and the number of co-authored papers is used to compute the rank of co-authors. Not every co-author is a Scholar co-author. Some don’t have accounts for example.
