From Research Models to Journalist's Browser: An RSE Story from a 140,000-user Verification Tool

Abstract

Disinformation and false content produced by generative AI often moves faster than journalists, fact-checkers and human rights defenders can verify. Across a decade of EU-funded projects - InVID (2016–2018), WeVerify (2018–2021), and vera.ai (2022–2025) - research groups have produced a steady stream of natural language processing (NLP) classifiers for persuasion techniques, subjectivity, AI-generated text, and more. Individually, each is a valuable research output. Yet together, they were unusable in a journalist’s daily workflow, being spread across papers, demos, and APIs that couldn’t talk to each other. The solution is the Verification Assistant, a component of the Verification Plugin published by Agence France-Presse (AFP), which bridges the “research-to-practice” gap. Maintained by RSEs at the University of Sheffield since 2023, it accepts a URL or media file, extracts content, routes it to NLP classifiers contributed by researchers across the project consortia, and returns one cohesive set of credibility indicators. Despite the vera.ai project ending in 2025, the Assistant and plugin remain in active use and continued maintenance. This is a real-world demonstration of research software outlasting the project that funded it. This talk uses the Assistant as a case study for what RSEs contribute to the research journey on a multi-institutional project. Without RSE input, journalists would not have access to these cutting edge research outputs to fight the spread of disinformation. I’ll cover the technical side (API services, architecture, software surviving handovers between teams) and the coordination side (working with researchers across institutions, the human side of building something collaboratively). Slides: https://docs.google.com/presentation/d/1a8jwge1i7Ww0G_sb0vOuyWmO6fiQdjc_CRRNMLxq4Ww/edit?usp=sharing Video: https://drive.google.com/file/d/1hfM9GC1vPKNCVDdvJfS5Xau_dapZYdt3/view?usp=sharing