RogueGPT: A Controlled Stimulus Generation Framework for News Authenticity Research

Python Submitted 13 June 2026Published 12 September 2026
Review

Editor: @crvernon (all papers)
Reviewers: @dosvk (all reviews), @prajwal-svm (all reviews)

Authors

Alexander Loth (0009-0003-9327-6865), Martin Kappes (0000-0002-8768-8359), Marc-Oliver Pahl (0000-0001-5241-3809)

Citation

Loth et al., (2026). RogueGPT: A Controlled Stimulus Generation Framework for News Authenticity Research. Journal of Open Source Software, 11(125), 11219, https://doi.org/10.21105/joss.11219

@article{Loth2026, doi = {10.21105/joss.11219}, url = {https://doi.org/10.21105/joss.11219}, year = {2026}, publisher = {The Open Journal}, volume = {11}, number = {125}, pages = {11219}, author = {Loth, Alexander and Kappes, Martin and Pahl, Marc-Oliver}, title = {RogueGPT: A Controlled Stimulus Generation Framework for News Authenticity Research}, journal = {Journal of Open Source Software} }
Copy citation string · Copy BibTeX  
Tags

misinformation fake news stimulus generation large language models research methodology natural language processing

Altmetrics
Markdown badge

 

License

Authors of JOSS papers retain copyright.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License

Table of Contents
Public user content licensed CC BY 4.0 unless otherwise specified.
ISSN 2475-9066