In today’s century, when someone shows us the news, video or pictures of any event, how can we believe its authenticity? It seems that the public is losing their trust in media due to the lack of reliable reference of facts.Addressing the problem of fake news requires a combination of technologies and a multi-faceted approach due to the social dimension.So, Our solution includes three main systems to fight against the dissemination of fake news,and to provide a way for society to recognize and uphold reality
Our Solution
- A Chrome extension for real-time analysis of the content in user’s feed for web based media platforms.
- A mechanism to check if an image or video is morphed or not.
- A Whatsapp Bot for social communities to use this feature of fake news detection.
- A mechanism for source tracking
- A user interface/website built on ReactJs Framework for specific fact checking of input links/texts/images.
- API : This folder has information about all machine learning models along with how to train them from scratch and also run in development server.
- Chrome extension : This folder contains the design information about the chrome extension which is built as a platform independent source to tackle fake news circulation.
- Morphed Image Classifier : To check if a given image has been morphed by someone, do refer to this folder.
- Spreadsheet update : Used to store the messages in whatsapp bot in spreadsheet.
- website-UI : This folder contains the design implementation of our website.
- Spreadsheet Update : This folder is for updating google sheet and retriving data from spreadsheet automatically
- Keras
- Flask
- Pytorch
- React
Please provide some screenshots/GIFs.
List all Future Works
- Analyze the video content more accurately to detect morphed or fake videos
- Implement XLNET, GPT-2, Roberta, Universal Sentence Encoder
- Text to Speech
- Regional Languages support in the Bot
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.
- Parth Halani (final Year B.Tech. at IIIT Guwahati)
- Gargee (final Year B.Tech. at IIIT Guwahati)
- Ashutosh Gupta (3rd Year B.Tech. at IIIT Guwahati)
- Sahil Bajaj (final Year B.Tech. at IIIT Guwahati)
- Saurav Bhartia (final Year B.Tech. at IIIT Guwahati)
- Ankit Jaglan (final Year B.Tech. at IIIT Guwahati)