Search

Results for "propaganda detection"

MultiProSE: A Multi-label Arabic Dataset for Propaganda, Sentiment, and Emotion Detection

arXiv · Feb 12

The paper introduces MultiProSE, the first multi-label Arabic dataset for propaganda, sentiment, and emotion detection. It extends the existing ArPro dataset with sentiment and emotion annotations, resulting in 8,000 annotated news articles. Baseline models, including GPT-4o-mini and BERT-based models, were developed for each task, and the dataset, guidelines, and code are publicly available. Why it matters: This resource enables further research into Arabic language models and a better understanding of opinion dynamics within Arabic news media.

Detecting Propaganda Techniques in Code-Switched Social Media Text

arXiv · May 23

This paper introduces a new task: detecting propaganda techniques in code-switched text. The authors created and released a corpus of 1,030 English-Roman Urdu code-switched texts annotated with 20 propaganda techniques. Experiments show the importance of directly modeling multilinguality and using the right fine-tuning strategy for this task.

The power of propaganda and AI’s ability to fight it

MBZUAI · Invalid Date

MBZUAI 2023 graduate Muhammad Umar is researching propaganda detection in low-resource, code-switched languages like Roman Urdu. His master's thesis focuses on detecting propaganda techniques in social media text using deep learning models. Umar aims to submit a paper on his findings to the EMNLP 2023 conference. Why it matters: This research addresses the under-explored area of propaganda detection in low-resource languages, which is crucial for combating misinformation in bilingual communities.