Repository files navigation

• Table of Contents
  • Introduction
  • News Cateogries
  • Architecture
  • System interface design
  • Poster
  • Demo-video
  • Tech stack
  • Project Deliverables
  • Installation
  • Prerequisites
    • How to run the app?
    • How to stop the Deep learning model servers?
  • Google colab notebook
  • Acknowledgement
  • Support me
  • Roadmap
  • Contributing
  • License
  • Contact
  • Contributors

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Fake news is playing an increasingly dominant role in spreading misinformation by influencing people’s perceptions or knowledge to distort their awareness and decision-making.

The growth of social media and online forums has spurred the spread of fake news causing it to easily blend with truthful information.

This study provides a novel text analytics–driven approach to fake news detection for reducing the risks posed by fake news consumption.

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Poster-01	Poster-02
PDF	PDF

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1. Programming Language : Python
2. Frontend : Streamlit
3. API : VirusTotal API
4. Platform : Colab notebook, Jupyter notebook, Visual studio code
5. Testing tool : Apache Jmeter, Google PageSpeed insights, Selenium
6. Machine learning Library : Tensorflow, PyTorch, Keras, Huggingface transformers, simpletransformers
7. Web framework : Flask
8. WSGI server : Gunicorn
9. Web server : Nginx
10. Cloud infrastructure support: AWS EC2 instance, AWS secret manager
11. Containerization/deployment: Docker

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TheProject Deliverables includes detailed documentation of the project, includingSoftware Requirement Specifications (SRS),Software Project Management Plan (SPMP),Software Design Description (SDD),Software Testing Document (STD),Implementation details, andResult and conclusion.

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Clone git repository

    $ git clone"https://github.com/hritik5102/Fake-news-classification-model"

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Run the setup file on git bash or any linux terminal:

$ bash setup.sh

Run the following commands:

1. bash start-server.sh on git bash or any linux terminalThis will start the deep learning model servers.

2. cd src

3. streamlit run app.py

runbash stop-server.sh on git bash or any linux terminal

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Filename	Notebook
GPT2 Model
BiLSTM + GloVe Model
BERT Model
Roberta Model

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Some resources have been used to build this project, so I'd like to acknowledge the resources in thereference section. Take a look.

If you think that I've referred any piece of code or material but have not acknowledged it. Please create an issue mentioning the site info & a link pointing to that material.

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See theopen issues for a list of proposed features (and known issues).

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Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make aregreatly appreciated.

Make sure your changes don't break existing functionality withoutgood reason.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Discuss the features, ideas you want to add to the project fromhere 📌

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Distributed under theMIT License. See LICENSE for more information.

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Project Link -hritik5102/Fake-news-classification-model (github.com)

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Thanks goes to these wonderful people 👏👏

Heet Sakaria 💻🤔📖🖋

vedangparasnis 💻📖

Viraj Thakkar 📖

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