language:
- en
pretty_name: elliquiy-rp_2023-04
size_categories:
- 100K<n<1M
configs:
- config_name: default
data_files:
- split: train
path: elliquiy-rp_2023-04_*.parquet
license: cc-by-4.0
Elliquiy roleplaying forum data
A collection of 6.6 million posts and 112 thousands forum threads from Elliquiy (arguably the largest and one of the oldest adult roleplaying forums on the Internet), from April 2005 through April 2023. About 9 GB of uncompressed text data (including formatting tags). The data was processed from the original source files that ended up composing a larger raw Forum RP dataset collection I also uploaded, but unlike those they don't have spacing issues between HTML tags.
Note that only solo and small-group roleplays ("games") and OOC threads from the "Play-By-Post" sections were scraped, not the various "social" sections.
Basic automated cleaning was performed, but the messages are still (by deliberate choice) in HTML format, with the notable exception of converting linebreaks into \n. In addition to the messages, some metadata was provided for user convenience, as well as alternative names that could be used instead of actual usernames (in the format of User0, User1 ... UserN). These are unique per-thread, but not globally.
Note: I might update the dataset in the future as I improve the cleaning procedure or the data format.
Limitations, quirks and issues
- During the scraping process (performed on April 2023) some information like text color and links got lost.
- Given the text formatting used by many users, automated conversion to Markdown seems very difficult without causing severe formatting problems.
- Most of the data has a sexual nature.
Basic dataset usage
The files need PyArrow installed from pip to be loaded with pandas. FastParquet will not work properly due to the nested data structure.
import pandas
# Load a parquet file into one DataFrame
df = pandas.read_parquet('elliquiy-rp_2023-04_00000-of-00006.parquet')
# Load the shareGPT-like message group from one specific row into a standard Python list
messages = list(df.iloc[2350].messages)
Consolidate the parquet files into one large DataFrame (requires large amounts of memory):
import glob
import pandas
filenames = sorted(glob.glob('*.parquet'))
parquets = []
# Read the parquet files one by one
for file in filenames:
parquets.append(pandas.read_parquet(file))
# Concatenate the parquet files into one DataFrame
full_df = pandas.concat(parquets)
Showing thread metadata from one specific row after loading the data:
In [2]: df.iloc[2350]
Out[2]:
thread-id 11897
thread-title The League of Extraordinary ...
category-id 65
category-name Noncon: Human-Freeform Solos
participant-count 3
message-count 242
word-count-total 35197
word-count-median 136.0
messages {'from': 'OrdinaryName', 'from-alternative': 'User...
Name: 2350, dtype: object
Dataset field explanation
Threads
| Field | Explanation |
|---|---|
| thread-id | The forum software's given thread id |
| thread-date | The date of the opening post in the thread |
| thread-title | User-given thread title |
| category-id | The id of the subforum where the thread was posted |
| category-name | The full name of the subforum. "Small Groups" subforums are dedicated to roleplays for more than two participants, and "Solo" are generally for two participants but more than two may appear here as well. |
| participant-count | The number of users writing in the thread |
| message-count | The total number of messages in the thread |
| word-count-total | The cumulative sum of space-separated words in the thread, calculated by python's split() function, including HTML tags |
| word-count-median | The median message length in words, calculated by python's split() function, including HTML tags |
Messages
| Field | Explanation |
|---|---|
| index | Message number, starting from zero at the beginning of the thread. Added mainly for debugging purposes |
| from | The name of the user who wrote the message. Avoid using if possible |
| from-alternative | Alternative, locally-unique name for the user in the form of User0 ... UserN |
| timestamp | ISO UTC message timestamp |
Message length analysis
Messages in older threads were in general shorter and more casually written than those in newer ones. This might be due to a slow shift over time in the userbase and/or self-selection due to access requirements.
Cleaning procedure details
At the HTML element level
- Simplified blockquotes
- Removed all attributes from most tags
- Cosmetic font sizes consolidated into three categories:
<small>, normal,<big>(deprecated tag) - Font changes removed
- Special CSS effects removed
- Background-colored text changed into
<mark> - Spoiler tags converted into
<details><summary>blocks- However, inline spoilers don't work well with this—to be checked out at a later time
- Removed left/right "floating"
<div> - Removed left/right/justify text-alignment
<div> - Center alignment
<div>changed to<center>(deprecated tag) - Recomposed URLs and their associated text into
<a>elements, when possible- The data was originally scraped using a forum function that decomposed
<a>links into text+URL
- The data was originally scraped using a forum function that decomposed
- Tried to reduce the amount of
<table>inappropriately used for presentation purposes- More work needed
At the text level
- Converted post dates to ISO format
- Removed non-standard unicode spaces
- Changed generic spoiler text
- Removed some leftover BB tags (most often the result of user error)
- More work needed
- Shortened some bare URLs
- Changed
elliquiy.comURLs intoexample.com - Removed some site-internal URLs
- Converted all smilies into emoji
- Removed excessive newlines and leading/trailing spaces
- Fixed some HTML element spacing issue
- More work needed
NOT done
- Replacing HTML escape characters
- Turning image URLs into
<img> - Balancing quote marks and other characters that are supposed to be paired
- Changing fancy punctuation to ASCII punctuation
- Removing usernames entirely from the dataset