Just out of curiosity, after Scihub now an analysis of papers commented at the PubPeer website. Pubpeer is now also screened on a regular basis by Holden Thorp, the chief editor of Science…
Unfortunately I am loosing many records for incomplete or malformed addresses, while some preliminary conclusions can already be made when looking at my world map.
A further revision will need to include more addresses and also overall research output as a reference.
Other country level data are also interesting. Just to name a few
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pubpeer[,"affiliation_list"] %>%
(function(x) {
strsplit(x,",") %>% sapply(., tail, 1) %>% unlist()
}) %>%
word(.,-1) %>%
as_tibble() %>%
mutate(value = gsub("[\\.]+", "",value)) %>%
mutate(value = gsub("PR.*", "China",value)) %>%
mutate( value = case_when
(value== "" ~ NA,
value== "States" ~ "USA",
value== "University" ~ NA,
value== "Republic" ~ NA,
value== "ROC" ~ NA,
value== "and" ~ NA,
value== "Maryland" ~ "USA",
value== "(mainland)" ~ "China",
value== "Kong" ~ "HongKong",
value== "Chemistry" ~ NA,
value== "Engineering" ~ NA,
value== "PAK" ~ "Pakistan",
value== "Arabia" ~ "South Arabia",
value== "Sciences" ~ NA,
value== "Technology" ~ NA,
value== "Medicine" ~ NA,
value== "NY" ~ "USA",
value== "America" ~ "USA",
value== "York" ~ "USA",
value== "Massachusetts" ~ "USA",
value== "Hospital" ~ NA,
value== "Zealand" ~ "New Zealand",
value== "Pennsylvania" ~ "USA",
value== "Africa" ~ "South Afria",
.default = value)) %>%
group_by(value) %>%
count(value) %>%
arrange( desc(n) ) %>%
rename(region=value) %>%
right_join(map_data('world'), by="region" ) %>%
filter(region != "Antarctica") %>%
ggplot() +
geom_polygon(aes(long, lat, group = group, fill = n)) +
coord_quickmap() +
scale_fill_gradient(name = "N", trans = "log10", breaks = c(10,100,1000), low = "black", high = "red", na.value = "lightgrey") +
theme_void()