@inproceedings{hasanain-etal-2023-qcri,
title = "{QCRI} at {S}em{E}val-2023 Task 3: News Genre, Framing and Persuasion Techniques Detection Using Multilingual Models",
author = "Hasanain, Maram and
El-Shangiti, Ahmed and
Nandi, Rabindra Nath and
Nakov, Preslav and
Alam, Firoj",
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-1.172",
doi = "10.18653/v1/2023.semeval-1.172",
pages = "1237--1244",
abstract = "Misinformation spreading in mainstream and social media has been misleading users in different ways. Manual detection and verification efforts by journalists and fact-checkers can no longer cope with the great scale and quick spread of misleading information. This motivated research and industry efforts to develop systems for analyzing and verifying news spreading online. The SemEval-2023 Task 3 is an attempt to address several subtasks under this overarching problem, targeting writing techniques used in news articles to affect readers{'} opinions. The task addressed three subtasks with six languages, in addition to three {``}surprise{''} test languages, resulting in 27 different test setups. This paper describes our participating system to this task. Our team is one of the 6 teams that successfully submitted runs for all setups. The official results show that our system is ranked among the top 3 systems for 10 out of the 27 setups.",
}
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<abstract>Misinformation spreading in mainstream and social media has been misleading users in different ways. Manual detection and verification efforts by journalists and fact-checkers can no longer cope with the great scale and quick spread of misleading information. This motivated research and industry efforts to develop systems for analyzing and verifying news spreading online. The SemEval-2023 Task 3 is an attempt to address several subtasks under this overarching problem, targeting writing techniques used in news articles to affect readers’ opinions. The task addressed three subtasks with six languages, in addition to three “surprise” test languages, resulting in 27 different test setups. This paper describes our participating system to this task. Our team is one of the 6 teams that successfully submitted runs for all setups. The official results show that our system is ranked among the top 3 systems for 10 out of the 27 setups.</abstract>
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%0 Conference Proceedings
%T QCRI at SemEval-2023 Task 3: News Genre, Framing and Persuasion Techniques Detection Using Multilingual Models
%A Hasanain, Maram
%A El-Shangiti, Ahmed
%A Nandi, Rabindra Nath
%A Nakov, Preslav
%A Alam, Firoj
%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 hasanain-etal-2023-qcri
%X Misinformation spreading in mainstream and social media has been misleading users in different ways. Manual detection and verification efforts by journalists and fact-checkers can no longer cope with the great scale and quick spread of misleading information. This motivated research and industry efforts to develop systems for analyzing and verifying news spreading online. The SemEval-2023 Task 3 is an attempt to address several subtasks under this overarching problem, targeting writing techniques used in news articles to affect readers’ opinions. The task addressed three subtasks with six languages, in addition to three “surprise” test languages, resulting in 27 different test setups. This paper describes our participating system to this task. Our team is one of the 6 teams that successfully submitted runs for all setups. The official results show that our system is ranked among the top 3 systems for 10 out of the 27 setups.
%R 10.18653/v1/2023.semeval-1.172
%U https://aclanthology.org/2023.semeval-1.172
%U https://doi.org/10.18653/v1/2023.semeval-1.172
%P 1237-1244
Markdown (Informal)
[QCRI at SemEval-2023 Task 3: News Genre, Framing and Persuasion Techniques Detection Using Multilingual Models](https://aclanthology.org/2023.semeval-1.172) (Hasanain et al., SemEval 2023)
ACL