Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    TypeError
Message:      Couldn't cast array of type string to null
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2361, in __iter__
                  for key, example in ex_iterable:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1882, in __iter__
                  for key, pa_table in self._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1905, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 499, in _iter_arrow
                  for key, pa_table in iterator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 346, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 106, in _generate_tables
                  yield f"{file_idx}_{batch_idx}", self._cast_table(pa_table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 73, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2223, in cast_table_to_schema
                  arrays = [
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2224, in <listcomp>
                  cast_array_to_feature(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in <listcomp>
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2052, in cast_array_to_feature
                  casted_array_values = _c(array.values, feature.feature)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1797, in wrapper
                  return func(array, *args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2086, in cast_array_to_feature
                  return array_cast(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1797, in wrapper
                  return func(array, *args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1948, in array_cast
                  raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
              TypeError: Couldn't cast array of type string to null

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

Bittensor Subnet 13 X (Twitter) Dataset

Data-universe: The finest collection of social media data the web has to offer
Data-universe: The finest collection of social media data the web has to offer

Miner Data Compliance Agreement

In uploading this dataset, I am agreeing to the Macrocosmos Miner Data Compliance Policy.

Dataset Summary

This dataset is part of the Bittensor Subnet 13 decentralized network, containing preprocessed data from X (formerly Twitter). The data is continuously updated by network miners, providing a real-time stream of tweets for various analytical and machine learning tasks. For more information about the dataset, please visit the official repository.

Supported Tasks

The versatility of this dataset allows researchers and data scientists to explore various aspects of social media dynamics and develop innovative applications. Users are encouraged to leverage this data creatively for their specific research or business needs. For example:

  • Sentiment Analysis
  • Trend Detection
  • Content Analysis
  • User Behavior Modeling

Languages

Primary language: Datasets are mostly English, but can be multilingual due to decentralized ways of creation.

Dataset Structure

Data Instances

Each instance represents a single tweet with the following fields:

Data Fields

  • text (string): The main content of the tweet.
  • label (string): Sentiment or topic category of the tweet.
  • tweet_hashtags (list): A list of hashtags used in the tweet. May be empty if no hashtags are present.
  • datetime (string): The date when the tweet was posted.
  • username_encoded (string): An encoded version of the username to maintain user privacy.
  • url_encoded (string): An encoded version of any URLs included in the tweet. May be empty if no URLs are present.

Data Splits

This dataset is continuously updated and does not have fixed splits. Users should create their own splits based on their requirements and the data's timestamp.

Dataset Creation

Source Data

Data is collected from public tweets on X (Twitter), adhering to the platform's terms of service and API usage guidelines.

Personal and Sensitive Information

All usernames and URLs are encoded to protect user privacy. The dataset does not intentionally include personal or sensitive information.

Considerations for Using the Data

Social Impact and Biases

Users should be aware of potential biases inherent in X (Twitter) data, including demographic and content biases. This dataset reflects the content and opinions expressed on X and should not be considered a representative sample of the general population.

Limitations

  • Data quality may vary due to the decentralized nature of collection and preprocessing.
  • The dataset may contain noise, spam, or irrelevant content typical of social media platforms.
  • Temporal biases may exist due to real-time collection methods.
  • The dataset is limited to public tweets and does not include private accounts or direct messages.
  • Not all tweets contain hashtags or URLs.

Additional Information

Licensing Information

The dataset is released under the MIT license. The use of this dataset is also subject to X Terms of Use.

Citation Information

If you use this dataset in your research, please cite it as follows:

@misc{James0962025datauniversex_dataset_58,
        title={The Data Universe Datasets: The finest collection of social media data the web has to offer},
        author={James096},
        year={2025},
        url={https://huggingface.co/datasets/James096/x_dataset_58},
        }

Contributions

To report issues or contribute to the dataset, please contact the miner or use the Bittensor Subnet 13 governance mechanisms.

Dataset Statistics

[This section is automatically updated]

  • Total Instances: 200892543
  • Date Range: 2006-01-04T00:00:00Z to 2025-06-19T00:00:00Z
  • Last Updated: 2025-07-11T04:03:59Z

Data Distribution

  • Tweets with hashtags: 19.69%
  • Tweets without hashtags: 80.31%

Top 10 Hashtags

For full statistics, please refer to the stats.json file in the repository.

Rank Topic Total Count Percentage
1 NULL 161336639 80.31%
2 #tiktok 709726 0.35%
3 #pr 431495 0.21%
4 #ad 407921 0.20%
5 #enhypen 357033 0.18%
6 #whalestorexoxo 333901 0.17%
7 #iran 286317 0.14%
8 #loveislandusa 276715 0.14%
9 #wearemadleen 247909 0.12%
10 #aiforall 244168 0.12%

Update History

Date New Instances Total Instances
2025-07-10T17:26:35Z 48 48
2025-07-10T17:26:42Z 50 98
2025-07-10T17:44:45Z 50 148
2025-07-11T04:03:59Z 200892395 200892543
Downloads last month
507