https://github.com/almayor/reddit-mods-dataset

A dataset of 25'834 largest communities on Reddit and their (anonymised) moderators.
https://github.com/almayor/reddit-mods-dataset

dataset graph graph-algorithms reddit social-network-analysis

Last synced: 20 days ago
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A dataset of 25'834 largest communities on Reddit and their (anonymised) moderators.

• Host: GitHub
• URL: https://github.com/almayor/reddit-mods-dataset
• Owner: almayor
• License: other
• Created: 2024-02-05T22:09:00.000Z (11 months ago)
• Default Branch: master
• Last Pushed: 2024-02-09T20:23:49.000Z (11 months ago)
• Last Synced: 2024-02-09T23:17:28.021Z (11 months ago)
• Topics: dataset, graph, graph-algorithms, reddit, social-network-analysis
• Language: Jupyter Notebook
• Homepage:
• Size: 27.5 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# RedditMods: Moderators of top-25'000 subreddits

![Kaggle](https://img.shields.io/badge/Kaggle-035a7d?style=for-the-badge&logo=kaggle&logoColor=white) ![Reddit](https://img.shields.io/badge/Reddit-%23FF4500.svg?style=for-the-badge&logo=Reddit&logoColor=white)

_RedditMods_ is a dataset that lists moderators of 25'834 largest and most popular communities on Reddit. The dataset is ideal for studying Reddit as a bipartite graph, where a moderator-node and a community-node are connected if the corresponding user moderates this subreddit. Clustering can then be performed to identify groups of subredits with a particular leaning, or to recommend similar communities.

## Data Collection

The data was scraped in the associated [Jupyter Notebook](code/reddit-mods-ds.ipynb). The data was publicly available and collected on 06 Feb 2024. All usernames were anonymised by hashing with SHA256, so that they cannot be linked to the moderators' Reddit accounts.

## Description of Files

The data is available both as a table and a bipartite graph.

#### GEXF – data in graph format

1. `graph.gexf`

	A bipartite graph, where nodes in the first group (having attribute `bipartite=0`) are moderators and nodes in the second group (having attribute `bipartite=1`) are subreddits. A moderator-node is connected with a subreddit-node if that moderator moderates this subreddit.

	

	Tags:

	* `size` on subreddit-nodes, indicating the number of subreddit's members

	  

	


	

#### CSV – data in table format


1. `subreddits.csv`

	Contains 25K subreddits from [Reddit's Top](www.reddit.com/best/communities/1/), combined with the [list](http://www.reddit.com/subreddits/) of Reddit's most popular communities. The two lists are not identical, as described in the [Jupyter notebook](code/reddit-mods-ds.ipynb). The headers are:

	* `name`: Name of subreddit

	* `n_members`: Number of members

	

	


	

2. `moderators.csv`


	Each row describes a subreddit-moderator pair:

	

	* `subreddit`: Name of subreddit

	* `moderator`: Username of moderator (anonymised by hashing)

	

	


3. `bots.csv`

	List of moderators that were identified as bots  by the primitive procedure, described in the previous section. These accounts were already removed from `moderators.csv`.

	

	* `name`: Username of bot

	


## Examples

* [Visualising a cluster of subreddits moderated by a group of users](./example/example.ipynb)



  

   



## Notes and warnings

I used a very simple procedure to filter out auto-moderators: (1) a short list of known bots (e.g. `u/AutoModerator`), (2) username starts or ends with `bot`. An additional procedure to identify and remove bots might be necessary. For an example, see [this notebook](example/example.ipynb).