Guess the Map 12: Or, How I Learned to Stop Worrying and Hate Mercator

unique visits or hack attempts

 

It is download events from a site.

 

Libgen?

 

So warm, you are nearly burning. Not quite that dodgy.

 

ResearchGate then?

 

No, I have not heard of them. You have to log in? Much freer than that. I am surprised, I would have thought it was much more famous that either you have mentioned. I have to go to bed soon.

 

You can give the win to Emzie and reveal the site/answer

 

Yeah, winner is @emzie well done.

Answer is paper downloads from Sci-Hub between Sept 2015 and Feb 2016. They host scientific primary literature and distribute it without respecting intellectual property rights. I think the trends shown are a function of level scientific enquiry and under-resourcedness of academic establishments in the respective countries. It is of note that while there most fervent enemies have won a claim US$15 million in damages (not paid), they have also recognised the creator as one of the ten people who most mattered in 2016, and wrote a very uncritical review of the usage statistics paper (which is found here). If this is how your worst enemies treat you, you have to be doing something right?

There is a feature length film about the problem and the solution, (licenced under CC BY 4.0 Creative Commons).

The creator, Alexandra Elbakyan




The paper with the raw data is here. The data is further analysed and commented on here, from whom I actually got the data I plotted.

Here is the code I used to generate the maps in case it is use to anyone, from this tutorial. It is in R, which is free as in speech and as in beer. It should be adaptable for other lists of features, but it seems the problem is matching up country names. There is a certain amount of data built in.

Spoiler Code :

Code:

# There is quite a bit to install, it takes quite a while compilling
if(F) {
  install.packages(c("cowplot", "googleway", "ggplot2", "ggrepel",
                     "ggspatial", "libwgeom", "sf", "rnaturalearth", "rnaturalearthdata")
  )
  install.packages("rgeos")
}

library("ggplot2")
theme_set(theme_bw())
library("sf")
library("rnaturalearth")
library("rnaturalearthdata")
library("rgeos")

world <- ne_countries(scale = "medium", returnclass = "sf")
head(world)

## From paper https://datadryad.org/stash/dataset/doi:10.5061/dryad.q447c
## Crunched by https://thewinnower.com/papers/4715-correlating-the-sci-hub-data-with-world-bank-indicators-and-identifying-academic-use

downloads <- read.table("https://raw.githubusercontent.com/gedankenstuecke/scihub_analysis/master/downloads_country.csv", quote="", sep = "\t", header = T, fill = T)

world$downloads <- downloads[match(world$name, trimws(as.character(downloads$Country))),"Downloads"]

# Debug missing countries
downloads[grepl("Croatia", downloads$Country),]
world[grepl("orea", world$name),"downloads"]
world[world$name == "Czech Rep.",]

# and fix them
world[world$name == "Korea","downloads"] <- downloads[grepl("Korea", downloads$Country),"Downloads"]
world[world$name == "Myanmar","downloads"] <- downloads[grepl("Myanmar", downloads$Country),"Downloads"]
world[world$name == "Czech Rep.","downloads"] <- downloads[grepl("Czech", downloads$Country),"Downloads"]

world$by_pop <- world$downloads / world$pop_est
world$Value <- world$downloads

png("first_go.png", width = 1900, height = 900)
ggplot(data = world) +
  geom_sf(aes(fill = Value), show.legend = NA) +
  scale_fill_viridis_c(option = "plasma", trans = "sqrt")
dev.off()

png("by_pop.png", width = 1900, height = 900)
ggplot(data = world) +
  geom_sf(aes(fill = by_pop), show.legend = NA) +
  scale_fill_viridis_c(option = "plasma", trans = "sqrt")
dev.off()

 

Last guess is sci hub lol

Edit: ha!

I'll make a map tomorrow

 

Great, now I have another site to leech uni papers from

 

My assumption is almost all the grey countries would actually be green if there was more data.

Edit: Sicily and Sardinia should be yellow like the rest of Italy.

 

This could have been about porn ^_^

 

Hey, the Axis is yellow.
(well, and some more)

Is it related to language?

 

Regulation of something.

 

You mean they regulate anything in Italy o_O ^^?

Related to alcohol or other legal drugs?

 

Nope.

Scale:

Red: illegal
Orange: illegal, with specific exemptions
Yellow: legal, but regulations have rendered most commercial activity unprofitable
Yellow-Green: legal, but most commercial activity illegal.
Green: legal

 

Can't be smoking, the Italians do a lot.
Can't be drinking, that should all be roughly the same.
Can't be Cannabis, because Netherlands is orange.
Can't be porn, should all be the same.
Can't be something with cars, because pretty sure Germany would be on one of the sides of the scale, not in the middle.

Ah... um, maybe about the lootboxes in computer games? Or gambling in general?

 

specifically online gambling?

 

I mean I checked maps with the status of prostitution, and that isn't the map.
Maybe gambling related, but again googled it and it seems it isn't.

 

Nothing so far. It's an industry, and the product is a vice of sorts, but not like drugs or gambling.

Places where it's illegal with exemptions (orange) are because the industry has traditionally been large.

 

Are green and light green specifically legal or legal because they are not regulated (yet?).
Are there any political links to this "thing"?

Have guns been mentioned yet?