Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/dementiy/vkr
Access to VK (Vkontakte) API via R
https://github.com/dementiy/vkr
api r vkontakte
Last synced: 24 days ago
JSON representation
Access to VK (Vkontakte) API via R
- Host: GitHub
- URL: https://github.com/dementiy/vkr
- Owner: Dementiy
- Created: 2015-03-30T19:26:04.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2020-09-25T17:50:21.000Z (about 4 years ago)
- Last Synced: 2024-10-01T10:02:24.735Z (about 1 month ago)
- Topics: api, r, vkontakte
- Language: R
- Size: 7.62 MB
- Stars: 56
- Watchers: 10
- Forks: 17
- Open Issues: 22
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
[](https://travis-ci.org/Dementiy/vkR)
[](https://cran.rstudio.com/web/packages/vkR/)
`vkR` is an R package which provides access to the [VKontakte](https://vk.com/) (VK) API.
## Installation
To get the current released version from CRAN:
```r
install.packages("vkR")
```
To get the current development version from github:
``` r
install.packages("devtools")
devtools::install_github("Dementiy/vkR")
library("vkR")
```
## Authorization
Most API requests require the use of an access token. VK has several types of authorization mechanisms. Check out the [documentation](https://vk.com/dev/authentication) for more details.
``` r
vkOAuth(CLIENT_ID, 'SCOPE', 'EMAIL', 'PASSWORD')
```
where:
* `CLIENT_ID` - is an application ID. You have to create new [Standalone-app](https://vk.com/dev/standalone) 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](https://vk.com/dev/permissions).
* `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:
``` r
setAccessToken(access_token = 'YOUR ACCESS TOKEN')
```
## Example of use
At your own risk you can use mongodb and [mongolite](https://github.com/jeroen/mongolite) package for storing data:
```r
> 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 232
```
If connection was aborted by some reasons we don't lose our data:
```r
> 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 3664
```
You can specify the collection name:
```r
> 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$items, use_db = TRUE, db_params=list('collection'='my_friends'), progress_bar = TRUE)
> show_collections()
db collection suffix count
1 temp data_mining_in_action wall 232
2 temp privivkanet wall 3664
3 temp dm posts 232
4 temp my_friends 141
```
For load collection into a namespace you can use `db_load_collection` function:
```r
> db_load_collection('data_mining_in_action', 'wall')
Imported 232 records. Simplifying into dataframe...
> ls()
[1] "temp.data_mining_in_action.wall"
> nrow(temp.data_mining_in_action.wall)
[1] 232
```
Building a Friend Graph:
``` r
my_friends <- getFriends(fields = 'sex')
my_friends <- filter(my_friends$items, is.na(deactivated))
network <- getNetwork(my_friends$id)
library("igraph")
g <- graph.adjacency(as.matrix(network), weighted = T, mode = "undirected")
layout <- layout.fruchterman.reingold(g)
plot(g, layout = layout)
```
Analyzing community activity:
``` r
domain <- 'nipponkoku'
wall <- getWallExecute(domain = domain, count = 0, progress_bar = TRUE)
metrics <- jsonlite::flatten(wall$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.