A promising European solution for the reliable, secure and personalized consumption of news content
New information reaches us every second. Different media flood people with content. It is becoming increasingly clear how difficult it has become to maintain an overview, to distinguish fake news from real news and at the same time to have up-to-date information at hand. It’s a good thing that there is already a solution. The Linz-based company Newsadoo has been one of the most promising media start-ups in Europe since it was founded in 2017 and is tackling precisely these challenges.
The Newsadoo product of the same name gives users access to numerous sources. They can consume news seamlessly across multiple digital devices, for example on desktop, mobile or via voice assistants. All devices are connected via the application.
At its heart is an intelligent algorithm that analyzes the user’s consumption behavior. It derives relevant correlations from the time, situation, device and content. On this basis, users receive personalized suggestions with relevant articles at any time. The recommender system is constantly evolving thanks to self-learning models.
For this mechanism to work reliably, a solid evaluation of the articles is required. This is why the system first processes and analyzes the texts automatically. Natural Language Processing (NLP) methods are used for this. They convert unstructured texts into structured, analyzable content.
Together with Newsadoo and SCCH, RISC Software GmbH is working on the TIDE (Transparent, Intelligent, Diverse, European News Recommendation Algorithm) project. The focus is on the further development of the recommendation algorithm. Research focuses on additional factors such as objectivity, reliability and diversity of content. These are intended to do justice to media diversity, prevent one-sided news consumption and create the greatest possible transparency.
RISC Software GmbH is happy to support you in the submission and implementation of (research) projects in the field of Natural Language Processing.
This project was funded by the Austrian Research Promotion Agency (FFG).
Data Scientist
