Baselight

Fake News Classification

Fake News Classification on WELFake Dataset

@kaggle.saurabhshahane_fake_news_classification

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About this Dataset

Fake News Classification

(WELFake) is a dataset of 72,134 news articles with 35,028 real and 37,106 fake news. For this, authors merged four popular news datasets (i.e. Kaggle, McIntire, Reuters, BuzzFeed Political) to prevent over-fitting of classifiers and to provide more text data for better ML training.

Dataset contains four columns: Serial number (starting from 0); Title (about the text news heading); Text (about the news content); and Label (0 = fake and 1 = real).

There are 78098 data entries in csv file out of which only 72134 entries are accessed as per the data frame.

Published in:
IEEE Transactions on Computational Social Systems: pp. 1-13 (doi: 10.1109/TCSS.2021.3068519).

Tables

Welfake Dataset

@kaggle.saurabhshahane_fake_news_classification.welfake_dataset
  • 144.97 MB
  • 72134 rows
  • 4 columns
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CREATE TABLE welfake_dataset (
  "unnamed_0" BIGINT,
  "title" VARCHAR,
  "text" VARCHAR,
  "label" BIGINT
);

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