Dataset Statistics
The training of this AI model used a dataset composed of news articles collected from the platform Veridica, a source that monitors and identifies fake news and misinformation, in combination with the open-source dataset FakeRom. The resulting dataset contains varied information, with each article being associated with a specific tag indicating its content type. This dataset was used to train a fake news classification model, which is used to generate the results above.
Tag Distribution
in the dataset
Predominant is: ""
items
Word Frequency
Limited to the top 100 most frequent words
Predominant is: ""
occurrences
0+ unique words
Content Length
by tag
Predominant tag: ""
NaN characters on average