DisTrack: Tracking disinformation in Online Social Networks through Deep Natural Language Processing (DisTrack)

Funding company


Our solution will provide benefits in the industrial field, including fact-checkers and journalists, among others, but it will also have a direct impact on society. In case of industrial transfer, our goal is to provide them with tools to increase the impact of their work, and to better assess the characteristics, detect the presence and track how hoaxes spread in Online Social Networks, enhancing fact-checkers’ work impact on society. Once a rumour or false claim has been detected by a fact-checker, our solution helps to track its presence in OSNs, a fundamental step in order to mitigate its propagation and to determine where the hoax is actually being shared, tracking its whole history, from the first appearances in OSNs to its current status. Our solution is independent from any OSN, being easily adapted to any of them, although it has been tested in Twitter so far.

Simultaneously, our platform is meant to directly help users, providing instruments to easily retrieve information from fact-checkers. With a web portal already developed and with a browser plugin currently under development, we aim to help users at verifying facts easily and efficiently, putting reliable information at their disposal. We seek to provide a versatile tool, easily adaptable to future requirements, such as retrieving information from different types of devices or applications. There are three key aspects to reach this: agile, concise and precise. Agile to reach the users before disinformation does, concise to avoid wasting the users time and keep their attention, and precise to ensure that the delivered information is useful.

Furthermore, our solution provides multilingual capabilities, which means that it is able to compare two pieces written in different languages, without needing translation. Additionally, our solution employs Artificial Intelligence based models which consider the context around a claim, which allows to perform a richer verification process.

Scope: Industrial
Funding support: 40000 €


Start date

November 1, 2021

End Date

December 31, 2022

Research areas


Principal investigator

Dr. Alejandro Martí­n


Universidad Politécnica de Madrid
Digital Future Society