UTB-NLP at SemEval-2023 Task 3: Weirdness, Lexical Features for Detecting Categorical Framings, and Persuasion in Online News

Jul 1, 2023·
Juan Cuadrado
,
Elizabeth Martinez
,
Anderson Morillo
,
Daniel Peña
,
Kevin Sossa
,
Juan Martinez-Santos
,
Edwin Puertas
· 0 min read
Abstract
Persuasive messages are increasingly prevalent on social networks, raising concerns across various communities. This study focuses on detecting news genre categories, framing, and persuasion techniques using lexical features. The proposed strategy leverages lexical weirdness to classify news articles as opinion pieces, factual reports, or satire. The approach was applied to subtasks 1 and 2 of SemEval 2023 Task 3.
Type
Publication
In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
Natural Language Processing Persuasion Detection Lexical Features News Classification