DOI: 10.5281/zenodo.14637313
title: MADOC: Multi-Platform Aggregated Dataset of Online Communities

description: The Multi-platform Aggregated Dataset of Online Communities (MADOC) is a comprehensive dataset that facilitates computational social science research by providing a unified, standardized dataset for cross-platform analysis of online social dynamics. MADOC aggregates and standardizes data from four distinct platforms: Bluesky, Koo, Reddit, and Voat, spanning from 2012 to 2024. The dataset includes 18.9 million posts, 236 million comments, and data from 23.1 million unique users across all platforms, with a particular focus on understanding community dynamics, user migration patterns, and the evolution of toxic behavior across platforms. By providing standardized data structures and FAIR-compliant access through Zenodo, MADOC enables researchers to conduct comparative analyses of user behavior, interaction networks, and content sentiment across diverse social media environments. The dataset's unique value lies in its cross-platform scope, standardized structure, and rich metadata, making it particularly suitable for studying societal phenomena such as community formation, toxic behavior propagation, and user migration patterns in response to platform moderation policies.
description: MADOC is a comprehensive dataset that facilitates computational social science research by providing a unified, standardized dataset for cross-platform analysis of online social dynamics. The dataset aggregates and standardizes data from four distinct platforms:





Reddit (2014-2020)

Voat (2013-2020)

Bluesky (2023-2024)

Koo (2020-2023)


Dataset Scale



18.9 million posts

236 million comments

23.1 million unique users across all platforms



Dataset Structure


The dataset is stored in Apache Parquet format, with separate files for each community. Each row represents a single interaction (post, comment, or repost) with the following standardized fields:

 




Field
Description


post_id 
Unique identifier for the interaction, anonymized






publish_date






UNIX timestamp of the interaction (seconds since epoch)








user_id






Anonymized identifier of the content creator








parent_id






Identifier of the parent post for comments/replies, NA for posts








parent_user_id






Identifier of the parent post's creator, NA for posts








content






Textual content of the interaction, with URLs extracted




url




External URLs referenced in the post/comment content




language




Detected language code (currently 'English' for all entries)




interaction_type




Type of interaction: 'POST', 'COMMENT', or 'REPOST'




platform








Source platform: 'reddit', 'voat', 'bluesky', or 'koo'






community








Community identifier (subreddit/subverse name), NA for Bluesky/Koo






sentiment_vader








VADER sentiment score ranging from -1 (negative) to 1 (positive)






sentiment_textblob








 TextBlob sentiment polarity score ranging from -1 (negative) to 1 (positive)






subjectivity_textblob








TextBlob subjectivity score ranging from 0.0 (objective) to 1.0 (subjective)






toxicity_togixen








 ToxiGen toxicity score ranging from 0.00 (non-toxic) to 1.00 (toxic)






strict_filter












Whether content matches strict keyword filtering criteria (1/0)











Platform Statistics


Reddit

 

Total interactions: 247.6M

Posts: 14.5M

Comments: 233.1M

Unique users: 22.6M

Average posts per user: 2.7

Average comments per user: 11.6

Mean sentiment: 0.063

URLs percentage: 10.3%


Voat

 

Total interactions: 1.2M

Posts: 0.4M

Comments: 0.8M

Unique users: 0.1M

Average posts per user: 8.5

Average comments per user: 7.8

Mean sentiment: 0.011

URLs percentage: 31.8%


Bluesky

 

Total interactions: 2.8M

Posts: 0.9M

Comments: 0.9M

Unique users: 0.2M

Average posts per user: 14.4

Average comments per user: 6.2

Mean sentiment: 0.088

URLs percentage: 4.5%


Koo

 

Total interactions: 4.3M

Posts: 3.1M

Comments: 1.2M

Unique users: 0.2M

Average posts per user: 23.0

Average comments per user: 10.6

Mean sentiment: 0.054

URLs percentage: 11.6%


Communities Covered
General Interest Communities



 

1. funny

2. gaming

3. pics

4. videos

5. gifs

6. technology


Controversial Communities

 

1. fatpeoplehate

2. GreatAwakening

3. MillionDollarExtreme

4. CringeAnarchy

5. KotakuInAction

6. MensRights


Responsible Usage Policy


By using this dataset, researchers agree to:


1. Research Purpose: Use the dataset solely for legitimate research purposes that aim to understand and improve online social dynamics.


2. Privacy Protection:

- Make no attempts to de-anonymize or re-identify users

- Not link or combine this dataset with other data sources to reveal user identities

- Not contact or attempt to identify individuals mentioned in post content


3. Ethical Research:

- Obtain appropriate institutional ethics approval when required

- Follow established guidelines for ethical social media research

- Consider potential impacts on marginalized or vulnerable communities


4. Prohibited Uses:

- Training harmful AI models or content generation systems

- Analyzing patterns to identify or target vulnerable communities


5. Publication Guidelines:

- Properly cite the dataset in any resulting publications

- Clearly document any filtering or processing applied to the data

- Share research findings responsibly, considering potential misuse
License

 

This dataset is released under Creative Commons Attribution International 4.0 License.

 

 




Right to Erasure (Right to be forgotten)

All users included in the MADOC dataset have the right to opt out and request the removal of their data, in accordance with GDPR provisions. However, the dataset was created for scientific research purposes, thereby falling under the scenarios for which GDPR provides derogations. The data has been thoroughly pseudonymized..

If you wish to have your interactions excluded from this dataset, please submit your request to madoc@ctrust.ac.rs. 

We will process your request as soon as possible.

 

 




 

Contact


You can reach us at: madoc@ctrust.ac.rs