@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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T UTB-NLP at SemEval-2023 Task 3: Weirdness, Lexical Features for Detecting Categorical Framings, and Persuasion in Online News
%A Cuadrado, Juan
%A Martinez, Elizabeth
%A Morillo, Anderson
%A Peña, Daniel
%A Sossa, Kevin
%A Martinez-Santos, Juan
%A Puertas, Edwin
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Da San Martino, Giovanni
%Y Tayyar Madabushi, Harish
%Y Kumar, Ritesh
%Y Sartori, Elisa
%S Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F cuadrado-etal-2023-utb
%X 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.
%R 10.18653/v1/2023.semeval-1.214
%U https://aclanthology.org/2023.semeval-1.214
%U https://doi.org/10.18653/v1/2023.semeval-1.214
%P 1551-1557
Markdown (Informal)
[UTB-NLP at SemEval-2023 Task 3: Weirdness, Lexical Features for Detecting Categorical Framings, and Persuasion in Online News](https://aclanthology.org/2023.semeval-1.214) (Cuadrado et al., SemEval 2023)
ACL
- Juan Cuadrado, Elizabeth Martinez, Anderson Morillo, Daniel Peña, Kevin Sossa, Juan Martinez-Santos, and Edwin Puertas. 2023. UTB-NLP at SemEval-2023 Task 3: Weirdness, Lexical Features for Detecting Categorical Framings, and Persuasion in Online News. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 1551–1557, Toronto, Canada. Association for Computational Linguistics.