https://github.com/knapply/tweetgraph
Model tweet data as various graph structures.
https://github.com/knapply/tweetgraph
Last synced: about 1 month ago
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Model tweet data as various graph structures.
- Host: GitHub
- URL: https://github.com/knapply/tweetgraph
- Owner: knapply
- License: gpl-3.0
- Created: 2019-09-06T12:20:32.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2019-10-18T00:33:47.000Z (over 6 years ago)
- Last Synced: 2025-01-16T03:14:24.535Z (over 1 year ago)
- Language: R
- Homepage: https://knapply.github.io/tweetgraph/
- Size: 9.26 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# `{tweetgraph}`
[](https://www.tidyverse.org/lifecycle/#experimental)
[](https://github.com/knapply/tweetgraph/commits/master)
[](https://codecov.io/gh/knapply/tweetgraph?branch=master)
[](https://ci.appveyor.com/project/knapply/tweetgraph)
[](https://travis-ci.org/knapply/tweetgraph)
[](https://www.gnu.org/licenses/gpl-3.0)
[](https://www.r-project.org/)
[](https://github.com/knapply/tweetgraph)
[](http://hits.dwyl.io/knapply/tweetgraph)
# Installation
``` r
# install.packages("remotes")
remotes::install_github("knapply/tweetgraph")
```
# Usage
``` r
library(tweetgraph)
hashtag_rstats <- rtweet::search_tweets("#rstats")
```
## Social Network Analysis
### `as_sna_primitive()`
``` r
sna_data <- as_sna_primitive(hashtag_rstats)
lapply(sna_data, names)
```
#> $edges
#> [1] "from" "to" "action" "status_id" "text" "source"
#> [7] "lang"
#>
#> $nodes
#> [1] "name" "timestamp_ms" "TWITTER_NAME"
#> [4] "screen_name" "location" "description"
#> [7] "url" "protected" "followers_count"
#> [10] "friends_count" "listed_count" "statuses_count"
#> [13] "favourites_count" "account_created_at" "verified"
#> [16] "profile_url" "account_lang" "node_class"
### Using `{igraph}`
``` r
as_sna_igraph(hashtag_rstats)
```
#> IGRAPH 6fdbb99 DN-- 68 176 --
#> + attr: name (v/c), timestamp_ms (v/n), TWITTER_NAME (v/c),
#> | screen_name (v/c), location (v/c), description (v/c), url (v/c),
#> | protected (v/l), followers_count (v/n), friends_count (v/n),
#> | listed_count (v/n), statuses_count (v/n), favourites_count
#> | (v/n), account_created_at (v/n), verified (v/l), profile_url
#> | (v/c), account_lang (v/l), node_class (v/c), action (e/c),
#> | status_id (e/c), text (e/c), source (e/c), lang (e/c)
#> + edges from 6fdbb99 (vertex names):
#> [1] 1075011651366199297->144592995 1075011651366199297->144592995
#> [3] 1075011651366199297->144592995 1075011651366199297->144592995
#> + ... omitted several edges
``` r
as_sna_igraph(sna_data)
```
#> IGRAPH 6fdca54 DN-- 68 176 --
#> + attr: name (v/c), timestamp_ms (v/n), TWITTER_NAME (v/c),
#> | screen_name (v/c), location (v/c), description (v/c), url (v/c),
#> | protected (v/l), followers_count (v/n), friends_count (v/n),
#> | listed_count (v/n), statuses_count (v/n), favourites_count
#> | (v/n), account_created_at (v/n), verified (v/l), profile_url
#> | (v/c), account_lang (v/l), node_class (v/c), action (e/c),
#> | status_id (e/c), text (e/c), source (e/c), lang (e/c)
#> + edges from 6fdca54 (vertex names):
#> [1] 1075011651366199297->144592995 1075011651366199297->144592995
#> [3] 1075011651366199297->144592995 1075011651366199297->144592995
#> + ... omitted several edges
``` r
sna_data %>%
as_sna_igraph() %>%
plot_vis_net()
```
### Using `{network}`
``` r
as_sna_network(hashtag_rstats)
```
#> Network attributes:
#> vertices = 68
#> directed = TRUE
#> hyper = FALSE
#> loops = TRUE
#> multiple = TRUE
#> bipartite = FALSE
#> total edges= 176
#> missing edges= 0
#> non-missing edges= 176
#>
#> Vertex attribute names:
#> account_created_at account_lang description favourites_count followers_count friends_count listed_count location node_class profile_url protected screen_name statuses_count timestamp_ms TWITTER_NAME url verified vertex.names
#>
#> Edge attribute names:
#> action lang source status_id text
``` r
as_sna_network(sna_data)
```
#> Network attributes:
#> vertices = 68
#> directed = TRUE
#> hyper = FALSE
#> loops = TRUE
#> multiple = TRUE
#> bipartite = FALSE
#> total edges= 176
#> missing edges= 0
#> non-missing edges= 176
#>
#> Vertex attribute names:
#> account_created_at account_lang description favourites_count followers_count friends_count listed_count location node_class profile_url protected screen_name statuses_count timestamp_ms TWITTER_NAME url verified vertex.names
#>
#> Edge attribute names:
#> action lang source status_id text
## Write Gephi-Friendly .graphml Files
``` r
target_file_path <- "~/gephi-tweets.graphml"
tweet_graph <- as_sna_igraph(hashtag_rstats)
write_graphml(g = tweet_graph, path = target_file_path)
```
### Opening with Gephi
1.
2.
3.
4.
## Knowledge Graph
### `as_kg_primitive()`
``` r
kg_data <- as_kg_primitive(hashtag_rstats)
lapply(kg_data, names)
```
#> $edges
#> [1] "source" "target" "time" "source_class"
#> [5] "action" "target_class"
#>
#> $nodes
#> [1] "name" "timestamp_ms" "created_at"
#> [4] "text" "source" "lang"
#> [7] "node_class" "TWITTER_NAME" "screen_name"
#> [10] "location" "description" "url"
#> [13] "protected" "followers_count" "friends_count"
#> [16] "listed_count" "statuses_count" "favourites_count"
#> [19] "account_created_at" "verified" "profile_url"
#> [22] "account_lang"
### Using `{igraph}`
``` r
as_kg_igraph(hashtag_rstats)
```
#> IGRAPH 720affa DN-- 247 851 --
#> + attr: name (v/c), timestamp_ms (v/n), created_at (v/n), text
#> | (v/c), source (v/c), lang (v/c), node_class (v/c), TWITTER_NAME
#> | (v/c), screen_name (v/c), location (v/c), description (v/c), url
#> | (v/c), protected (v/l), followers_count (v/n), friends_count
#> | (v/n), listed_count (v/n), statuses_count (v/n),
#> | favourites_count (v/n), account_created_at (v/n), verified
#> | (v/l), profile_url (v/c), account_lang (v/l), time (e/n),
#> | source_class (e/c), action (e/c), target_class (e/c)
#> + edges from 720affa (vertex names):
#> [1] 1184982560247631873->1184989314238894080
#> + ... omitted several edges
``` r
as_kg_igraph(kg_data)
```
#> IGRAPH 720b74e DN-- 247 851 --
#> + attr: name (v/c), timestamp_ms (v/n), created_at (v/n), text
#> | (v/c), source (v/c), lang (v/c), node_class (v/c), TWITTER_NAME
#> | (v/c), screen_name (v/c), location (v/c), description (v/c), url
#> | (v/c), protected (v/l), followers_count (v/n), friends_count
#> | (v/n), listed_count (v/n), statuses_count (v/n),
#> | favourites_count (v/n), account_created_at (v/n), verified
#> | (v/l), profile_url (v/c), account_lang (v/l), time (e/n),
#> | source_class (e/c), action (e/c), target_class (e/c)
#> + edges from 720b74e (vertex names):
#> [1] 1184982560247631873->1184989314238894080
#> + ... omitted several edges
``` r
kg_data %>%
as_kg_igraph() %>%
plot_vis_net()
```
### Using `{network}`
``` r
as_kg_network(hashtag_rstats)
```
#> Network attributes:
#> vertices = 247
#> directed = TRUE
#> hyper = FALSE
#> loops = TRUE
#> multiple = FALSE
#> bipartite = FALSE
#> total edges= 851
#> missing edges= 0
#> non-missing edges= 851
#>
#> Vertex attribute names:
#> account_created_at account_lang created_at description favourites_count followers_count friends_count lang listed_count location node_class profile_url protected screen_name source statuses_count text timestamp_ms TWITTER_NAME url verified vertex.names
#>
#> Edge attribute names:
#> action source source_class target_class time
``` r
as_kg_network(kg_data)
```
#> Network attributes:
#> vertices = 247
#> directed = TRUE
#> hyper = FALSE
#> loops = TRUE
#> multiple = FALSE
#> bipartite = FALSE
#> total edges= 851
#> missing edges= 0
#> non-missing edges= 851
#>
#> Vertex attribute names:
#> account_created_at account_lang created_at description favourites_count followers_count friends_count lang listed_count location node_class profile_url protected screen_name source statuses_count text timestamp_ms TWITTER_NAME url verified vertex.names
#>
#> Edge attribute names:
#> action source source_class target_class time