Svetlana Maslenkova, Clement Christophe, Marco AF Pimentel, Tathagata Raha, Muhammad Umar Salman, Ahmed Al Mahrooqi, Avani Gupta, Shadab Khan, Ronnie Rajan, Praveenkumar Kanithi. Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing. 2025.

Propaganda is a form of communication intended to influence the opinions and the mindset of the public to promote a particular agenda.With the rise of social media, propaganda has spread rapidly, leading to the need for automatic propaganda detection systems.Most work on propaganda detection has focused on high-resource languages, such as English, and little effort has been made to detect propaganda for low-resource languages.Yet, it is common to find a mix of multiple languages in social media communication, a phenomenon known as code-switching.Code-switching combines different languages within the same text, which poses a challenge for automatic systems.Considering this premise, we propose a novel task of detecting propaganda techniques in codeswitched text.To support this task, we create a corpus of 1,030 texts code-switching between English and Roman Urdu, annotated with 20 propaganda techniques at the fragment level.We perform a number of experiments contrasting different experimental setups, and we find that it is important to model the multilinguality directly rather than using translation as well as to use the right fine-tuning strategy.The code and the dataset are publicly available at https://github.com/mbzuai-nlp/ propaganda-codeswitched-text