Fake News Analysis and Detection Demo

This repository contains a demo for analyzing and detecting fake news. This web-app provides users with insights and relevant information to help them analyze and classify fake news.

Credit: This project uses TruFor, as the forensic framework for the given image, created by Guillaro, Fabrizio and Cozzolino, Davide and Sud, Avneesh and Dufour, Nicholas and Verdoliva, Luisa.

Installation and Usage

1. Clone the repository to your local machine:

git clone https://github.com/nbtin/fakenews-detection-demo.git

2. Navigate to the project directory:

cd fakenews-detection-demo

3. Build docker image (that requires around 15.4 GB of disk space and takes around 10 minutes to build with a good internet connection ~ 2x MB/s):

bash docker_build.sh

4. Run docker container:

• Running on your local (Linux) machine with Nvidia GPU support:

  docker run -it --name=thesis-demo -p 8501:8501 --runtime=nvidia --gpus all -v $(realpath ./):/thesis-demo/ thesis-demo bash
  

• Running on your local (Windows) machine with Nvidia GPU support:

  docker run -it --name=thesis-demo -p 8501:8501 --gpus all -v .:/thesis-demo/ thesis-demo bash

• Running on a server manually:

  # remember to replace <your_port> with your actual port number you want to map to the container port 8501.
  docker run -it --name=thesis-demo -p your_port:8501 --gpus all -v $(realpath ./):/thesis-demo/ thesis-demo bash

  • This command will let you enter the container with the bash shell.

  • You can run the following command to start the demo:

    streamlit run demo_docker.py

  • Then, go to server address with port <your_port> to see the demo.

• Running on a server with a script:

  sbatch run_demo.sh

  Then, go to server address with port 20333 to see the demo.

5. Additional steps for the first run:

Wait for the demo to start and open the link in your browser. You are required to wait for the cheapfakes and TruFor checkpoint to be downloaded in the first run (around 2.9GB) before the web ready.

6. Demo: