README.md

VTuber 500M: Live Chat and Moderation Events

VTuber 500M is a huge collection of hundreds of millions of live chat, super chat, and moderation events (ban and deletion) all across Virtual YouTubers' live streams, ready for academic research and any kind of NLP projects.

Download the dataset from Kaggle Datasets and join #livechat-dataset channel on holodata Discord for discussions.

Provenance

• Source: YouTube live chat events collected by our Honeybee cluster. Holodex is a stream index provider for Honeybee which covers Hololive, Nijisanji, 774inc, etc.
• Temporal Coverage:
  • Chats: from 2021-01-15T05:15:33Z
  • Superchats: from 2021-03-16T08:19:38Z
• Update Frequency:
  • At least once per month

Research Ideas

• Toxic Chat Classification
• Spam Detection
• Demographic Visualization
• Superchat Analysis
• Sentence Transformer for Live Chats

See public notebooks for ideas.

We employed Honeybee cluster to collect real-time live chat events across major Vtubers' live streams. All sensitive data such as author name or author profile image are omitted from the dataset, and author channel id is anonymized by SHA-1 hashing algorithm with a grain of salt.

Versions

Standard version

Standard version is available at Kaggle Datasets.

filename	summary	size
channels.csv	Channel index	< 1 MB
chat_stats.csv	Chat statistics	< 1 MB
superchat_stats.csv	Super Chat statistics	< 1 MB
chats_%Y-%m.csv	Live chat events (~ 500,000,000)	~ 50 GB
superchats_%Y-%m.csv	Super chat events (~ 2,000,000)	~ 200 MB
deletion_events.csv	Deletion events	~ 150 MB
ban_events.csv	Ban events	~ 25 MB

Full version

Full version is only available to those approved by the admins. If you are interested in conducting research or analysis using the dataset, please reach us at #livechat-dataset channel on holodata Discord server or at uechiy@acm.org (for organizations).

filename	summary	size
channels.csv	Channel index	< 1 MB
chat_stats.csv	Chat statistics	< 1 MB
superchat_stats.csv	Super Chat statistics	< 1 MB
chats_%Y-%m.csv	Live chat messages (~ 500,000,000)	~ 90 GB
superchats_%Y-%m.csv	Super chat messages (~ 2,000,000)	~ 400 MB
deletion_events.csv	Deletion events	~ 150 MB
ban_events.csv	Ban events	~ 25 MB

❤️‍🩹 Sensai

Sensai is a toxic chat dataset consists of live chats from Virtual YouTubers' live streams.

filename	summary	size
chats_flagged_%Y-%m.csv	Chats flagged as either deleted or banned by mods (3,100,000+)	~ 400 MB
chats_nonflag_%Y-%m.csv	Non-flagged chats (3,000,000+)	~ 300 MB

Dataset Breakdown

Ban and deletion are equivalent to markChatItemsByAuthorAsDeletedAction and markChatItemAsDeletedAction respectively.

Channels (channels.csv)

column	type	description
channelId	string	channel id
name	string	channel name
englishName	nullable string	channel name (English)
affiliation	string	channel affiliation
group	nullable string	group
subscriptionCount	number	subscription count
videoCount	number	uploads count
photo	string	channel icon

Inactive channels have INACTIVE in group column.

Chat Statistics (chat_stats.csv)

column	type	description
channelId	string	channel id
period	string	interested period (%Y-%M)
chats	number	number of chats
memberChats	number	number of chats with membership status attached
uniqueChatters	number	number of unique chatters
uniqueMembers	number	number of unique members appeared on live chat
bannedChatters	number	number of unique chatters marked as banned by mods
deletedChats	number	number of chats deleted by mods

Super Chat Statistics (superchat_stats.csv)

column	type	description
channelId	string	channel id
period	string	interested period (%Y-%M)
superChats	number	number of super chats
uniqueSuperChatters	number	number of unique super chatters
totalSC	number	total amount of super chats (JPY)
averageSC	number	average amount of super chat (JPY)
totalMessageLength	number	total message length
averageMessageLength	number	average mesage length
mostFrequentCurrency	string	most frequent currency
mostFrequentColor	string	most frequent color

Chats (chats_%Y-%m.csv)

column	type	description	in standard version
timestamp	string	ISO 8601 UTC timestamp	seconds are omitted
id	string	anonymized chat id	N/A
authorChannelId	string	anonymized author channel id
channelId	string	source channel id
videoId	string	source video id
body	string	chat message	N/A
membership	string	membership status	N/A
isMember	nullable boolean	is member (null if unknown)	only in standard version
isModerator	boolean	is channel moderator	N/A
isVerified	boolean	is verified account	N/A

Membership status

value	duration
unknown	Indistinguishable
non-member	0
less than 1 month	< 1 month
1 month	>= 1 month, < 2 months
2 months	>= 2 months, < 6 months
6 months	>= 6 months, < 12 months
1 year	>= 12 months, < 24 months
2 years	>= 24 months

Pandas usage

Set keep_default_na to False and na_values to '' in read_csv. Otherwise, chat message like NA would incorrectly be treated as NaN value.

chats = pd.read_csv('../input/vtuber-livechat/chats_2021-03.csv',
                    na_values='',
                    keep_default_na=False,
                    index_col='timestamp',
                    parse_dates=True)

Superchats (chats_:year:-:month:.csv)

column	type	description	in standard version
timestamp	string	ISO 8601 UTC timestamp	seconds are omitted
amount	number	purchased amount
currency	string	three-letter currency symbol
color	string	color	N/A
significance	number	significance
body	nullable string	chat message	N/A
id	string	anonymized chat id	N/A
authorChannelId	string	anonymized author channel id
videoId	string	source video id	N/A
channelId	string	source channel id

Color and Significance

color	significance	purchase amount (¥)	purchase amount ($)	max. message length
blue	1	¥ 100 - 199	$ 1.00 - 1.99	0
lightblue	2	¥ 200 - 499	$ 2.00 - 4.99	50
green	3	¥ 500 - 999	$ 5.00 - 9.99	150
yellow	4	¥ 1000 - 1999	$ 10.00 - 19.99	200
orange	5	¥ 2000 - 4999	$ 20.00 - 49.99	225
magenta	6	¥ 5000 - 9999	$ 50.00 - 99.99	250
red	7	¥ 10000 - 50000	$ 100.00 - 500.00	270 - 350

Pandas usage

Set keep_default_na to False and na_values to '' in read_csv. Otherwise, chat message like NA would incorrectly be treated as NaN value.

import pandas as pd
from glob import iglob

sc = pd.concat([
    pd.read_csv(f,
                na_values='',
                keep_default_na=False,
                index_col='timestamp',
                parse_dates=True)
    for f in iglob('../input/vtuber-livechat/superchats_*.csv')
],
               ignore_index=False)
sc.sort_index(inplace=True)

Deletion Events (deletion_events.csv)

column	type	description
timestamp	string	UTC timestamp
id	string	anonymized chat id
retracted	boolean	is deleted by author oneself
videoId	string	source video id
channelId	string	source channel id

Pandas usage

Insert deleted_by_mod column to chats DataFrame:

chats = pd.read_csv('../input/vtuber-livechat/chats_2021-03.csv',
                    na_values='',
                    keep_default_na=False)
delet = pd.read_csv('../input/vtuber-livechat/deletion_events.csv',
                    usecols=['id', 'retracted'])

delet = delet[delet['retracted'] == 0]

delet['deleted_by_mod'] = True
chats = pd.merge(chats, delet[['id', 'deleted_by_mod']], how='left')
chats['deleted_by_mod'].fillna(False, inplace=True)

Ban Events (ban_events.csv)

Here Ban means either to place user in time out or to permanently hide the user's comments on the channel's current and future live streams. This mixup is due to the fact that these actions are indistinguishable from others with the extracted data from markChatItemsByAuthorAsDeletedAction event.

column	type	description
timestamp	string	UTC timestamp
authorChannelId	string	anonymized channel id
videoId	string	source video id
channelId	string	source channel id

Pandas usage

Insert banned column to chats DataFrame:

chats = pd.read_csv('../input/vtuber-livechat/chats_2021-03.csv',
                    na_values='',
                    keep_default_na=False)
ban = pd.read_csv('../input/vtuber-livechat/ban_events.csv',
                  usecols=['authorChannelId', 'videoId'])

ban['banned'] = True
chats = pd.merge(chats, ban, on=['authorChannelId', 'videoId'], how='left')
chats['banned'].fillna(False, inplace=True)

Consideration

Anonymization

id and authorChannelId are anonymized by SHA-1 hashing algorithm with a pinch of undisclosed salt.

Handling Custom Emojis

All custom emojis are replaced with a Unicode replacement character U+FFFD.

Redundant Ban and Deletion Events

Bans and deletions from multiple moderators for the same person or chat will be logged separately. For simplicity, you can safely ignore all but the first line recorded in time order.

Citation

@misc{vtuber-livechat-dataset,
 author={Yasuaki Uechi},
 title={VTuber 500M: Large Scale Virtual YouTubers Live Chat Dataset},
 year={2021},
 month={3},
 version={31},
 url={https://github.com/holodata/vtuber-livechat-dataset}
}

License

• Code: MIT License
• Dataset: ODC Public Domain Dedication and Licence (PDDL)