Advanced AI tools for news analysis, bias detection, and media literacy.

Data-Informed Media Analysis Suite (DIMAS)

DIMAS is an AI-driven platform designed to empower journalists and the public by providing data-backed insights into news coverage, ensuring transparency and critical engagement with Maltese media.

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Funded by:

The DIMAS (Data-Informed Media Analysis Suite) project addresses the pressing need for tools that can navigate and critically assess the vast volume of modern news content. Developed by the Department of Artificial Intelligence at the University of Malta, DIMAS aims to enhance media literacy by providing a suite of AI-powered tools that detect bias and generate actionable insights from large-scale media datasets.

The project is built on three core pillars: Development, Interactivity, and Ethics. It involves the creation of advanced AI models for sentiment analysis and entity recognition, the launch of an interactive portal for both journalists and the general public, and the establishment of rigorous ethical guidelines for data handling. A unique aspect of DIMAS is its participation in the MDIA Technology Assurance Sandbox (TAS), which allows for the testing and refinement of these AI systems within a controlled regulatory framework to ensure reliability, safety, and compliance with emerging standards.

This project is financed by Xjenza Malta through the R&I Thematic Programmes: Digital Technologies Programme of 2025.

Why It Matters

Addressing Media Bias

DIMAS provides objective, AI-driven analysis to help users identify potential framing or sentiment biases in news reporting, fostering a more balanced media landscape.

Data-Driven Decision Making

By making over 500,000 articles semantically searchable, the suite enables journalists and researchers to validate facts and uncover long-term media trends with precision.

Powerful Analysis Features

Learn about the advanced AI techniques and methodologies powering our analysis system.

Bias and Insight Generation

The suite features custom-developed models trained to identify sentiment, extract key entities, and detect potential biases across a vast archive of Maltese news content.

Bias and Insight Generation

The suite features custom-developed models trained to identify sentiment, extract key entities, and detect potential biases across a vast archive of Maltese news content.