Journals
Investigative journalism for real-time news events that creates a healthy balance between human input and Artificial Intelligence . Humans even get rewarded!
Screenshots
Problem Statement
Journals is a news sharing platform with a mission to prioritise investigative journalism before sensationalism. The platform creates a healthy balance between human input and Artificial Intelligence where content is matched based on natural language processing and deep learning on video understanding.Our innovative incentivisation schema rewards contributors and journalists in a decentralized manner by distributing the funds received in our subscription model. The distribution uses quadratic funding to share more with news that hold more contributors.
Solution
The frontend is written in React with Typescript at the core. Our websockets are connecting with a custom blockchain written with Lisk (LSK) that enables use to properly manage user accounts and our subscription models. The frontend also connects with IPFS/Filecoin via Textile to enable decentralized content sharing for our news events. To top everything off, a python service is responsible for analysing our video content and text being shared to create a matching algorithm that can link small news events together.