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1.2 COMPUTER AND INFORMATION SCIENCE
Recent endeavours at detection of propaganda in news articles treat this as a fine-grained problem of detecting it within fragments; and hence, transformer based embeddings perform decently in such detection. We build our propaganda detection framework on top of a transformer model simultaneously enriching it with contextual linguistic information of surrounding part-of-speech tags and LIWC categories the word itself belongs to. The evaluation outcomes being encouraging indicate a huge potential for this line of reasoning in natural language processing of news text.
Younus, Arjumand and Qureshi, Muhammad Atif, "Combining BERT with Contextual Linguistic Features for Identification of Propaganda Spans in News Articles" (2020). Conference papers. 188.
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