@inproceedings{cuadrado-etal-2023-utb,
    title = "{UTB}-{NLP} at {S}em{E}val-2023 Task 3: Weirdness, Lexical Features for Detecting Categorical Framings, and Persuasion in Online News",
    author = "Cuadrado, Juan  and
      Martinez, Elizabeth  and
      Morillo, Anderson  and
      Pe{\~n}a, Daniel  and
      Sossa, Kevin  and
      Martinez-Santos, Juan  and
      Puertas, Edwin",
    editor = {Ojha, Atul Kr.  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Da San Martino, Giovanni  and
      Tayyar Madabushi, Harish  and
      Kumar, Ritesh  and
      Sartori, Elisa},
    booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.semeval-1.214",
    doi = "10.18653/v1/2023.semeval-1.214",
    pages = "1551--1557",
    abstract = "Nowadays, persuasive messages are more and more frequent in social networks, which generates great concern in several communities, given that persuasion seeks to guide others towards the adoption of ideas, attitudes or actions that they consider to be beneficial to themselves. The efficient detection of news genre categories, detection of framing and detection of persuasion techniques requires several scientific disciplines, such as computational linguistics and sociology. Here we illustrate how we use lexical features given a news article, determine whether it is an opinion piece, aims to report factual news, or is satire. This paper presents a novel strategy for news based on Lexical Weirdness. The results are part of our participation in subtasks 1 and 2 in SemEval 2023 Task 3.",
}

Nowadays, persuasive messages are more and more frequent in social networks, which generates great concern in several communities, given that persuasion seeks to guide others towards the adoption of ideas, attitudes or actions that they consider to be beneficial to themselves. The efficient detection of news genre categories, detection of framing and detection of persuasion techniques requires several scientific disciplines, such as computational linguistics and sociology. Here we illustrate how we use lexical features given a news article, determine whether it is an opinion piece, aims to report factual news, or is satire. This paper presents a novel strategy for news based on Lexical Weirdness. The results are part of our participation in subtasks 1 and 2 in SemEval 2023 Task 3.
Cuadrado, Juan Martinez, Elizabeth Morillo, Anderson Pe{\~n}a, Daniel Sossa, Kevin Martinez-Santos, Juan Puertas, Edwin
UTB-NLP at SemEval-2023 Task 3: Weirdness, Lexical Features for Detecting Categorical Framings, and Persuasion in Online News