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vosonSML - Social Media Lab

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The vosonSML R package is a suite of easy to use functions for collecting and generating different types of networks from social media data. The package supports the collection of data from the mastodon, reddit, youtube platforms and hyperlinks from web sites. Networks in the form of node and edge lists can be generated from collected data, supplemented with additional metadata, and used to create graphs for Social Network Analysis.

Installation Options

Installing the github version is recommended at this time as CRAN releases may occur less frequently.

  1. Install the latest github version:
# library(remotes)
remotes::install_github("vosonlab/vosonSML")
  1. Install the CRAN release version:
install.packages("vosonSML")

Getting started

The following usage examples will provide a quick start to using vosonSML functions. Additionally there is an Introduction to vosonSML vignette that is a practical and explanatory guide to collecting data and creating networks.

General Usage

The process of authentication, data collection and creating networks in vosonSML is expressed with the three functions: Authenticate, Collect and Create. The following are some examples of their usage for supported social media:

Mastodon | Reddit | YouTube | Hyperlink | Supplemental Functions

General Options

  • verbose: most vosonSML functions accept a verbosity parameter that is now set to TRUE by default. When FALSE functions will run silently unless there is a warning or error. If set to TRUE then progress and summary information for the function will be printed to the console.
  • writeToFile: vosonSML functions accept a write to file parameter. When set TRUE the collected data will be saved to a file in either the working directory or a directory set by the voson.data option. The file will be saved as a RDS file with a datetime generated name in the following format: YYYY-MM-DD_HHMMSS-XXXXXX as a rds or graphml file.

The following environment options can also be used:

  • voson.data: If set to an existing directory path the writeToFile output files will be written to that directory instead of the working directory. Can be set using options(voson.data = "~/vsml-data") for example, and is cleared by assigning a value of NULL. Directory paths can be relative to the working directory e.g. ./data or full paths.
  • voson.cat: If set to TRUE then the verbose output of functions will be printed using the base cat() function instead of the message() function. Set by entering options(voson.cat = TRUE), and clear by assigning a value of NULL.

Authentication

Authentication objects generally only need to be created once unless your credentials change. It is recommended to save your mastodon and youtube authentication objects to file after creation and then load them in future sessions.

Please note in the examples provided that the “~” notation in paths are short-hand for the system to use the users home directory, and the “.” at the start of file names signifies it as a hidden file on some OS. You can name and save objects however you wish.

# youtube data api key
youtube_auth <- Authenticate("youtube", apiKey = "xxxxxxxxxx")

# save the object after Authenticate
saveRDS(youtube_auth, file = "~/.auth_yt")

# load a previously saved authentication object for use in Collect
youtube_auth <- readRDS("~/.auth_yt")

Mastodon Usage

This implementation of mastodon collection uses the rtoot package and is most suited to collecting public posts.

Collect threads or search for posts from server timelines

Collect can be used to collect threads by setting the parameter endpoint = thread and providing the URL’s for the starting post of each thread to be collected. A mastodon server does not need to be specified, as the function will collect the thread posts from the server referenced in each URL.

The following example collects and combines all of the posts from the 3 threads provided. The result is a named list of two dataframes, one containing posts and one with the metadata for referenced users in the collection.

library(vosonSML)
options(voson.data = "./mast-data")

mast_auth <- Authenticate("mastodon")

# collect thread posts belonging to the supplied mastodon
# threads, the url of the first post in each thread should
# be used
mast_data <- mast_auth |>
  Collect(
    endpoint = "thread",
    threadUrls = c(
      "https://mastodon.social/@arstechnica/111257471648143532",
      "https://mastodon.social/@arstechnica/111257425856847171",
      "https://mastodon.social/@arstechnica/111257193332540480"
    ),
    writeToFile = TRUE
  )

# Collecting post threads for mastodon urls...
#
# id                 | created
# --------------------------------------------
# 111257471648143532 | 2023-10-18 18:38:11.509
# 111257731042879692 | 2023-10-18 19:44:08
# Collected 36 posts.
# RDS file written: ./mast-data/2023-10-18_201254-MastodonData.rds
# Done.

Collect posts or search and collect posts from server timelines

Collect with the parameter endpoint = search can be used to collect a number of the most recent posts, or the most recent posts containing a hashtag from server timelines. This function requires a server to be specified using the instance parameter.

The following example collect the most recent 100 posts made to the mastodon.social server local timeline. The local = TRUE parameter restricts posts to only those made by server users.

mast_data <- mast_auth |>
  Collect(
    endpoint = "search",
    instance = "mastodon.social",
    local = TRUE,
    numPosts = 100
  )

# Collecting timeline posts...
# Requested 100 posts
#
# id                 | created
# --------------------------------------------
# 111257854695457456 | 2023-10-18 20:15:36.349
# 111257844442617952 | 2023-10-18 20:12:59.92
# Collected 120 posts.
# Done.

The next example collects the most recent 100 posts from the mastodon.social server global timeline containing the hashtag #rstats. The global timeline includes posts made by users from mastodon.social as well as posts made by users on its affiliated servers. The global timeline is specified by setting local = FALSE.

mast_data <- mast_auth |>
  Collect(
    endpoint = "search",
    instance = "mastodon.social",
    local = FALSE,
    hashtag = "rstats",
    numPosts = 100,
    writeToFile = TRUE
  )

# Collecting timeline posts...
# Hashtag: rstats
# Requested 100 posts
# 
# id                 | created            
# ----------------------------------------
# 111851761879684588 | 2024-01-31 17:33:57
# 111839343172130565 | 2024-01-29 12:55:38
# Collected 120 posts.
# RDS file written: 2024-01-31_190125-MastodonData.rds
# Done.

Create mastodon activity and actor network graphs

The mastodon Create function accepts the data from Collect and a type parameter of activity or actor that specifies the type of network to create from the collected data. Create produces two dataframes, one for network nodes and one for node relations or edges. These can then be passed to the Graph function to produce an igraph object.

Activity network

Nodes are posts and edges are the relationship to other posts. The only relationship type supported at this time is reply edge.

net_activity <- mast_data |>
  Create("activity") |>
  AddText(mast_data) |>
  Graph()

# Generating mastodon activity network...
# Done.

# IGRAPH 7cc21ba DN-- 128 12 -- 
# + attr: type (g/c), name (v/c), post.created_at (v/n),
# | post.visibility (v/c), account.id (v/c), account.username
# | (v/c), account.acct (v/c), account.displayname (v/c),
# | user.avatar (v/c), post.tags (v/x), post.tags.urls (v/x),
# | post.reblogs_count (v/n), post.favourites_count (v/n),
# | post.replies_count (v/n), post.url (v/c), node_type (v/c),
# | absent (v/l), vosonTxt_post (v/c), created_at (e/n), edge_type
# | (e/c)
# + edges from 7cc21ba (vertex names):
# [1] 111851737032132167->111846251799585000
# + ... omitted several edges
Tag network

A variation on the mastodon activity network is the subtype tag. A tag network is a netork of tags (hashtags) found in posts, and their coocurrence with other tags within same posts used to create relations.

net_tag <- mast_data |>
   Create("activity", subtype = "tag") |>
   Graph()
   
# Generating mastodon activity network...
# Done.

# IGRAPH 23e6e20 DN-- 94 624 -- 
# + attr: type (g/c), name (v/c), post.id (e/c), edge_type (e/c)
# + edges from 23e6e20 (vertex names):
#  [1] peerreviewed   ->apackageaday    peerreviewed   ->oss            
#  [3] peerreviewed   ->rstats          apackageaday   ->peerreviewed   
#  [5] apackageaday   ->oss             apackageaday   ->rstats         
#  [7] oss            ->peerreviewed    oss            ->apackageaday   
#  [9] oss            ->rstats          rstats         ->peerreviewed   
# [11] rstats         ->apackageaday    rstats         ->oss            
# [13] rstats         ->reproducibility reproducibility->rstats         
# [15] rshiny         ->rstats          rstats         ->rshiny         
# + ... omitted several edges
Actor network

Nodes are authors of collected posts and edges are their relationship to other authors. The only relationship types supported at this time are reply and mention edges.

net_actor <- mast_data |>
  Create("actor", inclMentions = TRUE) |>
  AddText(mast_data) |>
  Graph()

# Generating mastodon actor network...
# Done.

# IGRAPH c46e984 DN-B 82 12 -- 
# + attr: type (g/c), name (v/c), user.acct (v/c), user.username
# | (v/c), user.displayname (v/c), user.url (v/c), user.avatar
# | (v/c), type (v/c), absent (v/l), post.id (e/c),
# | post.created_at (e/n), edge_type (e/c), vosonTxt_post (e/c)
# + edges from c46e984 (vertex names):
# [1] 109610301164555149->109610301164555149
# + ... omitted several edges
Server network

A variation on the mastodon actor network is the subtype server. A server network simply groups the users into single actors as represented by their servers, and similarly combines their relations at the server level.

net_server <- mast_data |>
   Create("actor", subtype = "server") |>
   Graph()

# Generating mastodon actor network...
# Done.

# IGRAPH 845c991 DN-- 23 10 -- 
# + attr: type (g/c), name (v/c), n (v/n), edge_type (e/c)
# + edges from 845c991 (vertex names):
#  [1] fosstodon.org  ->fosstodon.org   fosstodon.org  ->fosstodon.org  
#  [3] aus.social     ->aus.social      fosstodon.org  ->fosstodon.org  
#  [5] mastodon.social->mastodon.social fosstodon.org  ->fosstodon.org  
#  [7] fosstodon.org  ->fosstodon.org   fosstodon.org  ->fosstodon.org  
#  [9] mastodon.social->hachyderm.io    mstdn.social   ->mstdn.social

YouTube Usage

Authenticate and Collect comments from youtube videos

YouTube uses an API key rather than an OAuth token and is simply set by calling Authenticate with the key as a parameter.

# youtube authentication sets the api key
auth_yt <- Authenticate("youtube", apiKey = "xxxxxxxxxxxxxx")

Once the key is set then Collect can be used to collect the comments from specified youtube videos. The following example collects a maximum of 100 top-level comments and all replies from each of the 2 specified video ID’s. It produces a dataframe with the combined comment data.

video_url <- c("https://www.youtube.com/watch?v=AQzZNIyjyWM",
               "https://www.youtube.com/watch?v=lY0YLDZhT88&t=3152s")

collect_yt <- auth_yt |>
  Collect(videoIDs = video_url,
          maxComments = 100)
          
## Collecting comment threads for YouTube videos...
## Video 1 of 2
## ---------------------------------------------------------------
## ** Creating dataframe from threads of AQzZNIyjyWM.
## ** Collecting replies for 1 threads with replies. Please be patient.
## Comment replies 1 
## ** Collected replies: 1
## ** Total video comments: 11
## (Video API unit cost: 5)
## ---------------------------------------------------------------
## Video 2 of 2
## ---------------------------------------------------------------
## ** Creating dataframe from threads of lY0YLDZhT88.
## ** Collecting replies for 1 threads with replies. Please be patient.
## Comment replies 6 
## ** Collected replies: 6
## ** Total video comments: 14
## (Video API unit cost: 5)
## ---------------------------------------------------------------
## ** Total comments collected for all videos 25.
## (Estimated API unit cost: 10)
## Done.

Create youtube activity and actor network graphs

The youtube Create function accepts the data from Collect and a network type parameter of activity or actor.

Activity network

Nodes are video comments and edges represent whether they were directed to the video as a top-level comment or to another comment as a reply comment.

net_activity <- collect_yt |> Create("activity")

## Generating youtube activity network...
## -------------------------
## collected YouTube comments | 25
## top-level comments         | 18
## reply comments             | 7
## videos                     | 2
## nodes                      | 27
## edges                      | 25
## -------------------------
## Done.
g_activity <- net_activity |> Graph()

g_activity

## IGRAPH 5a9fb56 DN-- 27 25 -- 
## + attr: type (g/c), name (v/c), video_id (v/c), published_at (v/c),
## | updated_at (v/c), author_id (v/c), screen_name (v/c), node_type
## | (v/c), edge_type (e/c)
## + edges from 5a9fb56 (vertex names):
## [1] Ugw13lb0nCf4o4IKFb54AaABAg->VIDEOID:AQzZNIyjyWM
## [2] UgyJBlqZ64YnltQTOTt4AaABAg->VIDEOID:AQzZNIyjyWM
## [3] Ugysomx_apk24Pqrs1h4AaABAg->VIDEOID:AQzZNIyjyWM
## + ... omitted several edges
Actor network

Nodes are users who have posted comments and the video publishers, edges represent comments directed at other users.

net_actor <- collect_yt |> Create("actor")

## Generating YouTube actor network...
## Done.
g_actor <- net_actor |> Graph()

g_actor

## IGRAPH 5aad4c4 DN-- 24 27 -- 
## + attr: type (g/c), name (v/c), screen_name (v/c), node_type (v/c),
## | video_id (e/c), comment_id (e/c), edge_type (e/c)
## + edges from 5aad4c4 (vertex names):
##  [1] UCb9ElH9tzEkG9OxDIiSYgdg->VIDEOID:AQzZNIyjyWM
##  [2] UC0DwaB_wHNzUh-LA9sWXKYQ->VIDEOID:AQzZNIyjyWM
##  [3] UCNHA8SkizJKauefYt1FHmjQ->VIDEOID:AQzZNIyjyWM
## + ... omitted several edges

Reddit Usage

The reddit API end-point used by vosonSML does not require authentication but an Authenticate object is still used to set up the collection and creation operations as part of a reddit workflow.

Collect a thread listing from subreddit

By using the endpoint = "listing" parameter and a vector of subreddit names, a list of comment threads and their metadata can be collected. The number of list results returned per subreddit can be coarsely specified within 25 items, by using the max parameter.

# specify subreddit names
subreddits <- c("datascience")

# collect a listing of the 25 top threads by upvote of all time
collect_rd_listing <- Authenticate("reddit") |>
  Collect(endpoint = "listing", subreddits = subreddits,
          sort = "top", period = "all", max = 25,
          writeToFile = TRUE, verbose = TRUE)

## Collecting thread listing for subreddits...
## Waiting between 3 and 5 seconds per request.
## Request subreddit listing: datascience (max items: 25).
## subreddit_id | subreddit   | count
## ----------------------------------
## t5_2sptq     | datascience | 25   
## Collected metadata for 25 threads in listings.
## RDS file written: ./vsml-data/2023-04-02_073117-RedditListing.rds
## Done.

Collect reddit threads

The reddit Collect function can then be used to collect comments from reddit threads specified by URL’s.

# specify reddit threads to collect by url
thread_urls <- c(
  "https://www.reddit.com/r/datascience/comments/wcd8x5/",
  "https://www.reddit.com/r/datascience/comments/wcni2g/"
)

# or use permalinks from a previously collected listing
thread_urls <- collect_rd_listing$permalink |> head(n = 3)

# collect comment threads with their comments sorted by best comments first
collect_rd <- Authenticate("reddit") |>
  Collect(threadUrls = thread_urls,
          sort = "best", writeToFile = TRUE, verbose = TRUE)

## Collecting comment threads for reddit urls...
## Waiting between 3 and 5 seconds per thread request.
## Request thread: r/datascience (k8nyf8) - sort: best
## Request thread: r/datascience (oeg6nl) - sort: best
## Request thread: r/datascience (hohvgq) - sort: best
## HTML decoding comments.
## thread_id | title                                         | subreddit   | count
## -------------------------------------------------------------------------------
## hohvgq    | Shout Out to All the Mediocre Data Scienti... | datascience | 272  
## k8nyf8    | data siens                                    | datascience | 77   
## oeg6nl    | The pain and excitement                       | datascience | 179
## Collected 528 total comments.
## RDS file written: ./vsml-data/2023-04-02_073130-RedditData.rds
## Done.

Please note that because of the API end-point used that Collect is limited to the first 500 comments per thread (plus 500 for each continue thread encountered). It is therefore suited to collecting only smaller threads in their entirety.

Create reddit activity and actor networks

Activity network

Nodes are original thread posts and comments, edges are replies directed to the original post and to comments made by others.

# create an activity network
net_activity <- collect_rd |> Create("activity", verbose = TRUE)

## Generating reddit activity network...
## -------------------------
## collected reddit comments | 528
## subreddits                | 1 
## threads                   | 3 
## comments                  | 528
## nodes                     | 531
## edges                     | 528
## -------------------------
## Done.
g_activity <- net_activity |> Graph()

g_activity

## IGRAPH 62e8305 DN-- 531 528 -- 
## + attr: type (g/c), name (v/c), thread_id (v/c), comm_id (v/c),
## | datetime (v/c), ts (v/n), subreddit (v/c), user (v/c), node_type
## | (v/c), edge_type (e/c)
## + edges from 62e8305 (vertex names):
##  [1] k8nyf8.1      ->k8nyf8.0     k8nyf8.1_1    ->k8nyf8.1    
##  [3] k8nyf8.1_2    ->k8nyf8.1     k8nyf8.1_2_1  ->k8nyf8.1_2  
## + ... omitted several edges
Actor network

Nodes are reddit users who have commented on threads and edges represent replies to other users.

# create an actor network
net_actor <- collect_rd |> Create("actor", verbose = TRUE)

## Generating reddit actor network...
## -------------------------
## collected reddit comments | 528
## subreddits                | 1 
## threads                   | 3 
## comments                  | 273
## nodes                     | 321
## edges                     | 531
## -------------------------
## Done.
g_actor <- net_actor |> Graph()

g_actor

## IGRAPH 62fa45c DN-- 321 531 -- 
## + attr: type (g/c), name (v/c), user (v/c), subreddit (e/c), thread_id
## | (e/c), comment_id (e/n), comm_id (e/c)
## + edges from 62fa45c (vertex names):
##  [1] 1 ->1  2 ->1  3 ->1  1 ->3  3 ->1  4 ->1  5 ->1  6 ->3  7 ->1  8 ->7 
## [11] 9 ->1  1 ->9  10->1  11->1  1 ->11 1 ->1  1 ->1  1 ->1  1 ->1  1 ->1 
## + ... omitted several edges

Authenticate and Collect from web sites

The vosonSML hyperlink collection functionality does not require authentication as it is not using any web API’s, however an Authenticate object is still used to set up the collection and creation operations as part of the vosonSML workflow.

The hyperlink Collect function accepts a dataframe of seed web pages, as well as corresponding type and max_depth parameters for each page.

Please note that this implementalion of hyperlink collection and networks is still in an experimental stage.

# specify seed web pages and parameters for hyperlink collection
seed_pages <-
   tibble::tribble(
     ~page, ~type, ~max_depth,
     "http://vosonlab.net", "ext", 2,
     "https://www.oii.ox.ac.uk", "ext", 2,
     "https://sonic.northwestern.edu", "ext", 2
   )

#  A tibble: 3 × 3
#   page                           type  max_depth
#   <chr>                          <chr>     <dbl>
# 1 http://vosonlab.net            ext           2
# 2 https://www.oii.ox.ac.uk       ext           2
# 3 https://sonic.northwestern.edu ext           2

collect_web <- Authenticate("web") |>
  Collect(pages = seed_pages, verbose = TRUE)

# Collecting web page hyperlinks...
# *** initial call to get urls - http://vosonlab.net
# * new domain: http://vosonlab.net
# + http://vosonlab.net (10 secs)
# *** end initial call
# *** set depth: 2
# *** loop call to get urls - nrow: 6 depth: 2 max_depth: 2
# * new domain: http://rsss.anu.edu.au
# + http://rsss.anu.edu.au (0.96 secs)
# ...

Create activity and actor networks 

# generate a hyperlink activity network
net_activity <- collect_web |> Create("activity")

# generate a hyperlink actor network
net_actor <- collect_web |> Create("actor")

Supplemental Functions

Merge collected data together

The Merge and MergeFiles functions allow two or more Collect objects to be merged together provided they are of the same datasource type e.g mastodon.

get_hashtag_data <- function(tag) {
  Authenticate("mastodon") |>
    Collect(
      endpoint = "search",
      instance = "mastodon.social",
      local = FALSE,
      hashtag = tag,
      numPosts = 100,
      writeToFile = TRUE
    )
}

library(vosonSML)
options(voson.data = "./mast-data")

# collect data
mast_rstats <- get_hashtag_data("rstats")
mast_python <- get_hashtag_data("python")

# merge collect objects
data <- Merge(mast_rstats, mast_python, writeToFile = TRUE)

# Merging collect data...
# RDS file written: ./mast-data/2024-07-21_150353-MastodonDataMerge.rds
# Done.

# merge files from a data directory
data <- MergeFiles(
  "./mast-data", pattern = "*MastodonData.rds", writeToFile = TRUE
)

# Merging collect files...
# Matching files:
# - ./mast-data/2024-07-21_035919-MastodonData.rds
# - ./mast-data/2024-07-21_035925-MastodonData.rds
# Merging collect data...
# RDS file written: ./mast-data/2024-07-21_150544-DataMergeFile.rds
# Done.

AddText adds collected text data to networks as node or edge attributes

The AddText function can be used following the creation of all networks for mastodon, youtube and reddit. It will add an attribute starting with vosonTxt_ to nodes of activity networks and to edges of actor networks. It requires a collected datasource from which to extract text data.

# create activity network
net_activity <- data |> Create("activity")

# activity network with text data added as node attribute
net_activity <- net_activity |> AddText(data)
  
## Adding text data to network...Done.
names(net_activity)
#  [1] "post.id"               "post.created_at"      
# ..             
# [17] "vosonTxt_post"

AddText will also redirect some edges in a youtube actor network by finding user references at the beginning of reply comments text using the repliesFromText parameter. In the following example an edge would be redirected from UserC to UserB by text reference as opposed to UserA who made the top-level comment both users are replying to.

# video comments
# UserA: Great tutorial.
# |- UserB: I agree, but it could have had more examples.
# |- UserC: @UserB I thought it probably had too many.

Redirect edge between user nodes C -> A to C -> B.

# create activity network
net_actor <- collect_yt |> Create("actor")

# detects replies to users in text
net_actor <- net_actor |>
  AddText(collect_yt, repliesFromText = TRUE)

## Adding text data to network...Done.

AddVideoData requests and adds video data to networks

AddVideoData adds video information as node attributes in youtube actor networks and replaces the video ID nodes with a user (channel owner or publisher). The actorSubOnly parameter can be used to only perform the ID substitution.

# replaces VIDEOID:xxxxxx references in actor network with their publishers
# user id (channel ID) and adds additional collected youtube video info to actor
# network graph as node attributes
net_actor <- collect_yt |>
  Create("actor") |> 
  AddVideoData(auth_yt, actorSubOnly = FALSE)

names(net_actor)
## [1] "nodes"  "edges"  "videos"
nrow(net_actor$videos)
## [1] 2

AddVideoData function will also add a new dataframe to the actor_network network list containing the retrieved video information called videos.

g_actor <- net_actor |> Graph()

## IGRAPH 644cb17 DN-- 23 27 -- 
## + attr: type (g/c), name (v/c), screen_name (v/c), node_type (v/c),
## | video_id (e/c), comment_id (e/c), edge_type (e/c), video_title (e/c),
## | video_description (e/c), video_published_at (e/c)
## + edges from 644cb17 (vertex names):
## [1] UCb9ElH9tzEkG9OxDIiSYgdg->UCeiiqmVK07qhY-wvg3IZiZQ
## [2] UC0DwaB_wHNzUh-LA9sWXKYQ->UCeiiqmVK07qhY-wvg3IZiZQ
## + ... omitted several edges

Where to next?

Continue working with the network graphs using the igraph package and check out some examples of plots in the Introduction to vosonSML vignette. The graphml files produced by vosonSML are also easily imported into software such as Gephi for further visualization and exploration of networks.

As an alternative to vosonSML using the R command-line interface we have also developed an R Shiny app called VOSON Dash. It provides a user friendly GUI for the collection of data using vosonSML and has additional network visualization and analysis features.

For more detailed information about functions and their parameters, please refer to the Reference page.

Special thanks

This package would not be possible without a number of excellent packages created by others in the R community, we would especially like to thank the authors of the dplyr, httr2, igraph, RedditExtractoR, rtoot

Code of Conduct

Please note that the VOSON Lab projects are released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.