CC BY-NC-ND 4.0Grohnert, AnneAnneGrohnertBurkard, SimonSimonBurkardJohn, MichaelMichaelJohnGiertz, ChristianChristianGiertzKlose, StefanStefanKloseBillig, AndreasAndreasBilligSchmidt-Colberg, AmelieAmelieSchmidt-ColbergAbdullahi, MaryamMaryamAbdullahi2025-11-272025-11-272025-10https://publica.fraunhofer.de/handle/publica/499812https://doi.org/10.24406/publica-659010.5220/001377810000398510.24406/publica-65902-s2.0-105022256786Assessing the reliability of online news articles poses a significant challenge for users. This paper presents a novel digital platform that enables users to analyze German-language news articles based on various reliabilityrelated aspects, including opinion strength, sentiment, and article dissemination. Unlike many existing approaches focused solely on detecting fake news, this platform emphasizes the comparative analysis and visualization of relevant reliability indicators across articles from different publishers. The paper provides a comprehensive overview of the current state-of-art describing various existing approaches for the detection and presentation of disinformational online content before presenting the technical system architecture and user interfaces of the designed platform. A concluding user evaluation reveals some limitations and opportunities for further developments, but showed generally positive feedback on the platform's diverse analysis criteria and visual presentation to support users in assessing the credibility of news articles. Potential future applications range from evaluating article neutrality to verifying citations in academic contexts.enfalseOnline News VerificationWeb Information AnalysisFake News DetectionDisinformationReliabilityconference paper