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vkR is an R package which provides access to the VKontakte (VK) API.
To get the current released version from CRAN:
install.packages("vkR")To get the current development version from github:
install.packages("devtools")
devtools::install_github("Dementiy/vkR")
library("vkR")Most API requests require the use of an access token. VK has several types of authorization mechanisms. Check out the documentation for more details.
vkOAuth(CLIENT_ID, 'SCOPE', 'EMAIL', 'PASSWORD')where: * CLIENT_ID - is an application ID. You have to
create new Standalone-app in
VK to get ID (or use the already existing). * SCOPE - the
list of comma separated access rights,
e.g. 'friends,groups'- provide the access to user friends
and groups. List of all rights can be found here. * EMAIL and
PASSWORD - username and password.
If the EMAIL and PASSWORD have been
omitted, a browser window will be opened. In the address bar an access
token will be shown. Access token must be copied and passed as an
argument into the following function:
setAccessToken(access_token = 'YOUR ACCESS TOKEN')At your own risk you can use mongodb and mongolite package for storing data:
> db_init()
> wall <- getWallExecute(domain="data_mining_in_action", count=0, use_db=TRUE, progress_bar=TRUE)
|======================...======================| 100%
> show_collections()
db collection suffix count
1 temp data_mining_in_action wall 232If connection was aborted by some reasons we don’t lose our data:
> wall <- getWallExecute(domain='privivkanet', count=0, use_db = T, progress_bar = T)
|================= | 25%
Show Traceback
Rerun with Debug
Error in curl::curl_fetch_memory(url, handle = handle) :
Operation was aborted by an application callback ...
> show_collections()
db collection suffix count
1 temp data_mining_in_action wall 232
2 temp privivkanet wall 916
> wall <- getWallExecute(domain='privivkanet', count=0, offset=916, use_db = T, progress_bar = T)
|======================...======================| 100%
> show_collections()
db collection suffix count
1 temp data_mining_in_action wall 232
2 temp privivkanet wall 3664You can specify the collection name:
> wall <- getWallExecute(domain="data_mining_in_action", count=0,
use_db=TRUE, db_params=list('collection'='dm', 'suffix'='posts'), progress_bar=TRUE)
|======================...======================| 100%
> show_collections()
db collection suffix count
1 temp data_mining_in_action wall 232
2 temp privivkanet wall 3664
3 temp dm posts 232
> friends <- getFriends()
> users <- getUsersExecute(friends$items, use_db = TRUE, db_params=list('collection'='my_friends'), progress_bar = TRUE)
> show_collections()
db collection suffix count
1 temp data_mining_in_action wall 232
2 temp privivkanet wall 3664
3 temp dm posts 232
4 temp my_friends 141For load collection into a namespace you can use
db_load_collection function:
> db_load_collection('data_mining_in_action', 'wall')
Imported 232 records. Simplifying into dataframe...
> ls()
[1] "temp.data_mining_in_action.wall"
> nrow(temp.data_mining_in_action.wall)
[1] 232Building a Friend Graph:
my_friends <- getFriends(fields = 'sex')
my_friends <- filter(my_friends$items, is.na(deactivated))
network <- getNetwork(my_friends$id)
library("igraph")
g <- graph.adjacency(as.matrix(network), weighted = T, mode = "undirected")
layout <- layout.fruchterman.reingold(g)
plot(g, layout = layout)Analyzing community activity:
domain <- 'nipponkoku'
wall <- getWallExecute(domain = domain, count = 0, progress_bar = TRUE)
metrics <- jsonlite::flatten(wall$posts[c("date", "likes", "comments", "reposts")])
metrics$date <- as.POSIXct(metrics$date, origin="1970-01-01", tz='Europe/Moscow')
library(dplyr)
df <- metrics %>%
mutate(period = as.Date(cut(date, breaks='month'))) %>%
group_by(period) %>%
summarise(likes = sum(likes.count), comments = sum(comments.count), reposts = sum(reposts.count), n = n())
library(ggplot2)
library(tidyr)
ggplot(data=gather(df, 'type', 'count', 2:5), aes(period, count)) + geom_line(aes(colour=type)) +
labs(x='Date', y='Count')
You can find more examples in examples directory.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.