https://github.com/asubedi2001/fakenewsdetection

Misinformation classifier for social media content. We aim to use a Long Short Term Memory Model (LSTM) with attention to classify text as containing misinformation or not.

https://github.com/asubedi2001/fakenewsdetection

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Repository

Misinformation classifier for social media content. We aim to use a Long Short Term Memory Model (LSTM) with attention to classify text as containing misinformation or not.

Basic Info
  • Host: GitHub
  • Owner: asubedi2001
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 74.7 MB
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Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme

README.md

FakeNewsDetection

Binary and Multi-class misinformation classifiers based on LIAR dataset. We aim to LSTM, BiLSTM, GRU, and Transformer models to classify text which may contain misinformation or 'Fake News'

Dataset

LIAR: LIAR is a publicly available dataset for fake news detection. A decade-long of +12.K manually labeled short statements were collected in various contexts from POLITIFACT.COM, which provides detailed analysis report and links to source documents for each case. This dataset can be used for fact-checking research as well. Notably, this new dataset is an order of magnitude larger than previously largest public fake news datasets of similar type. The LIAR dataset4 includes 12.8K human labeled short statements from POLITIFACT.COM’s API, and each statement is evaluated by a POLITIFACT.COM editor for its truthfulness. Source: “Liar, Liar Pants on Fire”: A New Benchmark Dataset for Fake News Detection

Data pulled from https://paperswithcode.com/dataset/liar

Owner

  • Name: Aakash
  • Login: asubedi2001
  • Kind: user
  • Location: Maryland

UMBC Computer Science '24

GitHub Events

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Last Year
  • Delete event: 4
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  • Push event: 31
  • Public event: 1
  • Pull request event: 8
  • Create event: 4