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chwenjun225/top_5_insurance_brands_june_news_and_twitter_only

Top 5 Insurance Brands June News and Twitter Only A brief description of the dataset and its purpose. Dataset Summary Provide a summary of the dataset, including its size, the type of data it contains, and any other relevant information. Supported Tasks and Leaderboards List the tasks that this dataset supports and any associated leaderboards. Languages English Dataset Structure Data Instances Provide an… See the full description on the dataset page: https://huggingface.co/datasets/chwenjun225/top_5_insurance_brands_june_news_and_twitter_only.

sourceHugging Faceccupdated 2y agoView on Hugging Face
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Dataset Card

Top 5 Insurance Brands June News and Twitter Only

A brief description of the dataset and its purpose.

Dataset Summary

Provide a summary of the dataset, including its size, the type of data it contains, and any other relevant information.

Supported Tasks and Leaderboards

List the tasks that this dataset supports and any associated leaderboards.

Languages

English

Dataset Structure

Data Instances

Provide an example of a data instance in the dataset.

Data Fields

Describe the fields present in the dataset.

Data Splits

Explain how the dataset is split into training, validation, and test sets.

Dataset Creation

Curation Rationale

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Source Data

  • —Initial Data Collection and Normalization: Describe how the data was collected and normalized.
  • —Who are the source data producers? Provide information about the data producers.

Annotations

  • —Annotation process: Describe the annotation process.
  • —Who are the annotators? Provide information about the annotators.

Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

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Contributions

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Example Usage

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python
from datasets import load_dataset

dataset = load_dataset("your_dataset_name")

# Example usage
print(dataset["train"][0])