Follow the below instructions to run the solution.
1. Locate and open the FakeNewsDetection-starter.ipynb notebook from the Jupyter Notebook browser window.
2. Execute cells in the notebook by selecting
Cell --> Run All from Menu bar
For configuring with your data,
1. Place your csv data file with columns as 'text' and 'label' containing the 'text data' and 'predicted label' respectively as in the sample 'fakenews.csv' in the
fakenews-detection-master directory from the
kit_installer.bat location.
2. Replace the filename in the
'Variables' section of the notebook to your csv file name.
3. Execute cells in the notebook by selecting
Cell --> Run All from Menu bar.
Input file: fakenews.csv - contains sample data for Training and Predicting fake news. It has 2 columns : 'text' and 'label'.
Attributes of fakenews.csv dataset:
1.
text: text of the article
2.
label: a label that marks the article as potentially unreliable with 2 values '1' and '0'
1: fake
0: true
You can additionally try developing more ML models and include more enhancements for additional scores.
For any support, you can direct message us at
#help-with-kandi-kits