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  ## Dataset Structure
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  ### Data Instances
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  For each instance, there is a string for the title, a string for the article and a label to mark if it's true or false. See the [CNN / Daily Mail dataset viewer](https://huggingface.co/datasets/viewer/?dataset=fake_news&config=3.0.0) to explore more examples.
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  ## Dataset Creation
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- This dataset was created with python, using pandas library as the main processing data.
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- ### Curation Rationale
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- [More Information Needed]
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  ### Source Data
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  The source data is a mix of multiple fake_news datasets in Kaggle, a platform for train your skills and learnings about Artificial Intelligence. The main datasets who are based this dataset are:
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  Version 1.0.0 aimed to support supervised neural methodologies for deep learning and study the new Transformers models in the Natural Language Processing with News of the United States.
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- #### Who are the source language producers?
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- [More Information Needed]
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  ### Annotations
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  #### Annotation process
 
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  ## Dataset Structure
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+ The structure of this dataSet is composed by 40587 fields about News. This fields are composed by three types of fields; title of the news, the text or content of the news, and finally, the value of the news, who said if the new are fake (0) or true (1).
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  ### Data Instances
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  For each instance, there is a string for the title, a string for the article and a label to mark if it's true or false. See the [CNN / Daily Mail dataset viewer](https://huggingface.co/datasets/viewer/?dataset=fake_news&config=3.0.0) to explore more examples.
 
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  ## Dataset Creation
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+ This dataset was created with python, using pandas library as the main processing data. Also, this dataset are the mix of other datasets which are the same scope, the Fake News.
 
 
 
 
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  ### Source Data
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  The source data is a mix of multiple fake_news datasets in Kaggle, a platform for train your skills and learnings about Artificial Intelligence. The main datasets who are based this dataset are:
 
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  Version 1.0.0 aimed to support supervised neural methodologies for deep learning and study the new Transformers models in the Natural Language Processing with News of the United States.
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  ### Annotations
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  #### Annotation process