Proceedings:
No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations
Volume
Issue:
Proceedings of the AAAI Conference on Artificial Intelligence, 36
Track:
AAAI Student Abstract and Poster Program
Downloads:
Abstract:
We propose INDEPROP, a novel Natural Language Processing (NLP) application for combating online disinformation by mitigating propaganda from news articles. INDEPROP (Information-Preserving De-propagandization) involves fine-grained propaganda detection and its removal while maintaining document level coherence, grammatical correctness and most importantly, preserving the news articles’ information content. We curate the first large-scale dataset of its kind consisting of around 1M tokens. We also propose a set of automatic evaluation metrics for the same and observe its high correlation with human judgment. Furthermore, we show that fine-tuning the existing propaganda detection systems on our dataset considerably improves their generalization to the test set.
DOI:
10.1609/aaai.v36i11.21594
AAAI
Proceedings of the AAAI Conference on Artificial Intelligence, 36