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.
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
Mention if the dataset contains any personal or sensitive information.
Considerations for Using the Data
Social Impact of Dataset
Discuss the potential social impact of the dataset.
Discussion of Biases
Mention any known biases in the dataset.
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
Provide an example of how to use the dataset with the Hugging Face library:
from datasets import load_dataset
dataset = load_dataset("your_dataset_name")
# Example usage
print(dataset["train"][0])