Datasets:
The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ParserError
Message: Error tokenizing data. C error: Expected 1 fields in line 14, saw 2
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 233, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2998, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1918, in _head
return _examples_to_batch(list(self.take(n)))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2093, in __iter__
for key, example in ex_iterable:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1576, in __iter__
for key_example in islice(self.ex_iterable, self.n - ex_iterable_num_taken):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 279, in __iter__
for key, pa_table in self.generate_tables_fn(**gen_kwags):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/csv/csv.py", line 190, in _generate_tables
for batch_idx, df in enumerate(csv_file_reader):
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
return self.get_chunk()
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
return self.read(nrows=size)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1923, in read
) = self._engine.read( # type: ignore[attr-defined]
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
chunks = self._reader.read_low_memory(nrows)
File "parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
File "parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
File "parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 14, saw 2Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
A larger version of YT-100K dataset -> YT-30M dataset with 30 million YouTube multilingual multicategory comments is also available which can be obtained by directly emailing the author of this dataset.
Introduction
This work introduces two large-scale multilingual comment datasets, YT-30M (and YT-100K) from YouTube. The code and both the datasets: YT-30M (full) and YT-100K (randomly selected 100K sample from YT-30M) are publicly released for further research. YT-30M (YT-100K) contains 32M (100K) comments posted by YouTube channel belonging to YouTube categories. Each comment is associated with a video ID, comment ID, commenter name, commenter channel ID, comment text, upvotes, original channel ID and category of the YouTube channel (e.g., News & Politics, Science & Technology, etc.).
Data Description
Each entry in the dataset is related to one comment for a specific YouTube video in the related category with the following columns: videoID, commentID, commenterName, commenterChannelID, comment, votes, originalChannelID, category. Each field is explained below:
videoID: represents the video ID in YouTube.
commentID: represents the comment ID.
commenterName: represents the name of the commenter.
commenterChannelID: represents the ID of the commenter.
comment: represents the comment text.
votes: represents the upvotes received by that comment.
originalChannelID: represents the original channel ID who posted the video.
category: represents the category of the YouTube video.
Data Anonymization
The data is anonymized by removing all Personally Identifiable Information (PII).
Data sample
{
"videoID": "ab9fe84e2b2406efba4c23385ef9312a",
"commentID": "488b24557cf81ed56e75bab6cbf76fa9",
"commenterName": "b654822a96eae771cbac945e49e43cbd",
"commenterChannelID": "2f1364f249626b3ca514966e3ef3aead",
"comment": "ich fand den Handelwecker am besten",
"votes": 2,
"originalChannelID": "oc_2f1364f249626b3ca514966e3ef3aead",
"category": "entertainment"
}
Multilingual data
| Language | Text |
|--------------|---------------------------------------------------|
| English | You girls are so awesome!! |
| Russian | Точно так же Я стрелец |
| Hindi | आज भी भाई कʏ आवाज में वही पुरानी बात है.... |
| Chinese | 無論如何,你已經是台灣YT訂閱數之首 |
| Bengali | খুিন হািসনােক ভারেতর àধানমন্... |
| Spanish | jajajaj esto tiene que ser una brom |
| Portuguese | nossa senhora!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!... |
| Malayalam | നമസ്കാരം |
| Telegu | నమసాక్రం |
| Japanese | こんにちは |
License
[CC] (https://choosealicense.com/licenses/cc-by-4.0/#)
Bibtex
@misc{dutta2024yt30mmultilingualmulticategorydataset,
title={YT-30M: A multi-lingual multi-category dataset of YouTube comments},
author={Hridoy Sankar Dutta},
year={2024},
eprint={2412.03465},
archivePrefix={arXiv},
primaryClass={cs.SI},
url={https://arxiv.org/abs/2412.03465},
}
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