  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. With this in mind, here we
propose the novel task of detecting propaganda techniques in code-switched
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, which
we make publicly available. 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
