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Are statistics sexy? Visualising social networks certainly is! I wrote a little function, which makes producing beautiful plots depicting a mailbox with R an extremely easy task. I find visualisations of ‘social graphs’ particularly appealing. They look like flowers.

I had to use a few Python functions which can be executed within R with rJython library. The function connects to IMAP server and looks for “To:” and “From:” sections in stored emails. It should not be difficult to adapt this script to work with POP3 too. I am really impressed by what R can do (with a little bit of help from Python). Can anyone suggest a more elegant way to do the same thing without executing Python?

As rJython depends on rJava I had to install Java Development kit to launch it.

Warning: For me this function worked very well and did not do any harm to my mailbox. Despite that I am not an expert in IMAP so if you are going  to run it you are doing it at your own risk.

Here is the function:

mailSoc <- function(login,
pass,
serv = "imap.gmail.com", #specify IMAP server
ntore = 50, #ignore if addressed to more than
begin = -1){  #from which to start

require(rJython)
rJython <- rJython(modules = "imaplib")
rJython$exec("import imaplib") #connect to server rJython$exec(paste("mymail = imaplib.IMAP4_SSL('",
serv, "')", sep = ""))
rJython$exec(paste("mymail.login(\'", login, "\',\'", pass, "\')", sep = "")) #get number of available messages rJython$exec("sel = mymail.select()")
rJython$exec("number = sel[1]") nofmsg <- .jstrVal(rJython$get("number"))
nofmsg <- as.numeric(unlist(strsplit(nofmsg, "'"))[2])

#if 'begin' not specified begin from the newest
if(begin == -1)
{
begin <- nofmsg
}

if(todow == -1)
{
end <- 1
}
else
{
end <- begin - todow
}

#give a little bit of information
print(paste("Found", nofmsg, "emails"))
print("It can take a while")

data <- data.frame()

#fetching emails
for (i in begin:end) {
nr <- as.character(i)

#get sender
rJython$exec(paste("typ, fro = mymail.fetch(\'", nr, "\', \'(BODY[HEADER.FIELDS (from)])\')", sep = "")) rJython$exec("fro = fro[0][1]")
from <- .jstrVal(rJython$get("fro")) from <- unlist(strsplit(from, "[<>\r\n, \"]")) from <- sub("from: ", "", from, ignore.case = TRUE) from <- grep("@", from, value = TRUE) #get addresees rJython$exec(paste("typ, to = mymail.fetch(\'", nr, "\', \'(BODY[HEADER.FIELDS (to)])\')", sep = ""))
rJython$exec("to = to[0][1]") to <- .jstrVal(rJython$get("to"))
to <- unlist(strsplit(to, "[<>\r\n, \"]"))
to <- sub("to: ", "", to, ignore.case = TRUE)
from <- sub("\"", "", from, ignore.case = TRUE)
to  <- grep("@", to, value = TRUE)

if(length(to) <= ntore){
vec <- rep(from, length(to))
data <- rbind(data, data.frame(vec, to))
}

if((i - begin) %% 100 == 0)
{
}
}
names(data) <- c("from", "to")
data$from <- tolower(data$from)
data$to <- tolower(data$to)

#close connection
rJython$exec("mymail.shutdown()") return(data) } Now we can run eg. #download 200 most recent emails from gmail account maild <- mailSoc("login", "password", serv = "imap.gmail.com", ntore = 40, todow = 200) And to make a plot it is necessary to load network library library(network) mailnet <- network(maild) plot(maild) This is the result: R provides many other social network analysis tools such as igraph library. For instance, it can be used to make an interactive ‘plot’: library(igraph) h <- graph.data.frame(maild, directed = FALSE) tkplot(h, vertex.label = V(h)$name,
layout=layout.fruchterman.reingold)

I would like to learn more about SNA as well as I would like to try out Gephi which can produce visualisations which are even more attractive than those made in R so I think that I will write about my first impression soon.