Results of a survey of 403 discord users. The selection was random, the servers were random, a lot of people refused to go through, but someone agreed. Interrogated only Russian-speaking people. When creating, I notified users that after completion I was going to analyze the data and post the results in the public domain. No any personal user data was collected either.

In general, you can see that I like the discord, as well as some of the psychological focus of the questions. I have no experience in doing something like this, but still I tried to do everything as correctly as possible.

This version is translated into English. Also cleaned data and removed or changed something that wasn't needed.

We're excited to introduce Riffusion Share-Riff — a curated metadata and message dataset sourced from the Share-Riff channel of the Riffusion Discord server. This dataset highlights the creative output of the Riffusion community by collecting AI-generated songs and user messages. Using responsible scraping practices, we’ve gathered 17,000 messages, representing all user activity up to June 30, 2025. Monthly updates are planned to ensure the dataset remains current and captures the evolution of… See the full description on the dataset page: https://huggingface.co/datasets/sleeping-ai/riffusion-discord.

We're excited to introduce SunoV1 Messages — a curated metadata and message dataset sourced from the sunov1 channel of the Suno Discord server. This dataset captures the raw creative energy of the Suno community, collecting shared AI-generated songs and discussions from its active users. Using responsible scraping practices, we’ve gathered 138,267 messages, covering all user activity up to June 30, 2025. We plan to release monthly updates to ensure the dataset stays fresh and reflective of the… See the full description on the dataset page: https://huggingface.co/datasets/sleeping-ai/sunoV1-discord.

This Dataset is described in Charting the Landscape of Online Cryptocurrency Manipulation. IEEE Access (2020), a study that aims to map and assess the extent of cryptocurrency manipulations within and across the online ecosystems of Twitter, Telegram, and Discord. Starting from tweets mentioning cryptocurrencies, we leveraged and followed invite URLs from platform to platform, building the invite-link network, in order to study the invite link diffusion process.

Please, refer to the paper below for more details.

Nizzoli, L., Tardelli, S., Avvenuti, M., Cresci, S., Tesconi, M. & Ferrara, E. (2020). Charting the Landscape of Online Cryptocurrency Manipulation. IEEE Access (2020).

This dataset is composed of:

~16M tweet ids shared between March and May 2019, mentioning at least one of the 3,822 cryptocurrencies (cashtags) provided by the CryptoCompare public API;

~13k nodes of the invite-link network, i.e., the information about the Telegram/Discord channels and Twitter users involved in the cryptocurrency discussion (e.g., id, name, audience, invite URL);

~62k edges of the invite-link network, i.e., the information about the flow of invites (e.g., source id, target id, weight).

With such information, one can easily retrieve the content of channels and messages through Twitter, Telegram, and Discord public APIs.

Please, refer to the README file for more details about the fields.

Dataset Card for Midjourney User Prompts & Generated Images (250k)

  Dataset Summary





  General Context

Midjourney is an independent research lab whose broad mission is to "explore new mediums of thought". In 2022, they launched a text-to-image service that, given a natural language prompt, produces visual depictions that are faithful to the description. Their service is accessible via a public Discord server, where users interact with a Midjourney bot. When issued… See the full description on the dataset page: https://huggingface.co/datasets/nateraw/midjourney-texttoimage.

We're excited to introduce Suno Showcase — a curated metadata and message dataset sourced from the Suno Discord’s Showcase channel. This dataset captures the vibrant creativity of the Suno community by collecting songs and messages shared by users. Using responsible scraping practices, we've compiled 381,650 messages, covering all user activity up to June 30, 2025. We plan to release monthly updates to keep the dataset fresh and reflective of the evolving community. We provide the following… See the full description on the dataset page: https://huggingface.co/datasets/sleeping-ai/suno-discord.

Discord Scam / Clean Messages Dataset

A small but carefully-curated dataset for binary text-classification:

“Is this Discord message trying to scam / spam users?”

It is intended as a starting point for fine-tuning lightweight BERT-style models that moderate real-time chat servers.

  1 Origin & Collection

Source servers – private Discord communities (11 k members in total) run by the author. Period – 2024-01-01 → 2025-06-01. Extraction – Discord.py script iterated… See the full description on the dataset page: https://huggingface.co/datasets/wangyuancheng/discord-phishing-scam.

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Source

This data was provided by the website: https://place.thatguyalex.com/ And pulled using the code created here: https://github.com/ProstoSanja/place-2022

History

From Wikipedia: On March 28, 2022, a reboot of Place was announced. It began on April 1, 2022, and lasted for four days. Unlike in 2017, individual subreddits immediately began to coordinate pixel art; in large part due to this, and the increased number of users on Reddit between the two experiments. Different communities collaborated and formed alliances through Discord as well as subreddits. Large streamers on Twitch also participated by instructing thousands of their viewers to mark their logos and symbols. In response to the project's popularity, Reddit doubled the canvas's size and expanded the color palette on days 2 and 3. On the fourth day, the palette was reduced to only white, with which the entire canvas was blanked.

This Dataset

The dataset contains png images taken as snapshots of the r/place canvas throughout the 4 days it was online. The current version is final_v1 provided by https://place.thatguyalex.com/

Dataset Card for Unsupervised Peoples Speech

  Dataset Description





  Dataset Summary

The Unsupervised Peoples Speech Dataset is a compilation of audiofiles extracted from Archive.org that is licensed for academic and commercial usage under CC-BY and CC-BY-SA licenses. It includes more than one million hours of audio with a diverse set of speakers.

Point of Contact: MLCommons Datasets Discord

  Dataset Structure

This dataset is a collection of audio… See the full description on the dataset page: https://huggingface.co/datasets/MLCommons/unsupervised_peoples_speech.

Glaive-code-assistant

Glaive-code-assistant is a dataset of ~140k code problems and solutions generated using Glaive’s synthetic data generation platform. The data is intended to be used to make models act as code assistants, and so the data is structured in a QA format where the questions are worded similar to how real users will ask code related questions. The data has ~60% python samples. To report any problems or suggestions in the data, join the Glaive discord