@inproceedings{siino-2024-mcrock,
title = "{M}c{R}ock at {S}em{E}val-2024 Task 4: Mistral 7{B} for Multilingual Detection of Persuasion Techniques In Memes",
author = "Siino, Marco",
editor = {Ojha, Atul Kr. and
Do{\u{g}}ru{\"o}z, A. Seza and
Tayyar Madabushi, Harish and
Da San Martino, Giovanni and
Rosenthal, Sara and
Ros{\'a}, Aiala},
booktitle = "Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.semeval-1.9/",
doi = "10.18653/v1/2024.semeval-1.9",
pages = "53--59",
abstract = "One of the most widely used content types in internet misinformation campaigns is memes. Since they can readily reach a big number of users on social media sites, they are most successful there. Memes used in a disinformation campaign include a variety of rhetorical and psychological strategies, including smearing, name-calling, and causal oversimplification, to achieve their goal of influencing the users. The shared task{'}s objective is to develop models for recognizing these strategies solely in a meme{'}s textual content (Subtask 1) and in a multimodal context where both the textual and visual material must be analysed simultaneously (Subtasks two and three). In this paper, we discuss the application of a Mistral 7B model to address the Subtask one in English. Find the persuasive strategy that a meme employs from a hierarchy of twenty based just on its ``textual content.'' Only a portion of the reward is awarded if the technique{'}s ancestor node is chosen. This classification issue is multilabel hierarchical. Our approach based on the use of a Mistral 7B model obtains a Hierarchical F1 of 0.42 a Hierarchical Precision of 0.30 and a Hierarchical Recall of 0.71. Our selected approach is able to outperform the baseline provided for the competition."
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<abstract>One of the most widely used content types in internet misinformation campaigns is memes. Since they can readily reach a big number of users on social media sites, they are most successful there. Memes used in a disinformation campaign include a variety of rhetorical and psychological strategies, including smearing, name-calling, and causal oversimplification, to achieve their goal of influencing the users. The shared task’s objective is to develop models for recognizing these strategies solely in a meme’s textual content (Subtask 1) and in a multimodal context where both the textual and visual material must be analysed simultaneously (Subtasks two and three). In this paper, we discuss the application of a Mistral 7B model to address the Subtask one in English. Find the persuasive strategy that a meme employs from a hierarchy of twenty based just on its “textual content.” Only a portion of the reward is awarded if the technique’s ancestor node is chosen. This classification issue is multilabel hierarchical. Our approach based on the use of a Mistral 7B model obtains a Hierarchical F1 of 0.42 a Hierarchical Precision of 0.30 and a Hierarchical Recall of 0.71. Our selected approach is able to outperform the baseline provided for the competition.</abstract>
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%0 Conference Proceedings
%T McRock at SemEval-2024 Task 4: Mistral 7B for Multilingual Detection of Persuasion Techniques In Memes
%A Siino, Marco
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Tayyar Madabushi, Harish
%Y Da San Martino, Giovanni
%Y Rosenthal, Sara
%Y Rosá, Aiala
%S Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
%D 2024
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F siino-2024-mcrock
%X One of the most widely used content types in internet misinformation campaigns is memes. Since they can readily reach a big number of users on social media sites, they are most successful there. Memes used in a disinformation campaign include a variety of rhetorical and psychological strategies, including smearing, name-calling, and causal oversimplification, to achieve their goal of influencing the users. The shared task’s objective is to develop models for recognizing these strategies solely in a meme’s textual content (Subtask 1) and in a multimodal context where both the textual and visual material must be analysed simultaneously (Subtasks two and three). In this paper, we discuss the application of a Mistral 7B model to address the Subtask one in English. Find the persuasive strategy that a meme employs from a hierarchy of twenty based just on its “textual content.” Only a portion of the reward is awarded if the technique’s ancestor node is chosen. This classification issue is multilabel hierarchical. Our approach based on the use of a Mistral 7B model obtains a Hierarchical F1 of 0.42 a Hierarchical Precision of 0.30 and a Hierarchical Recall of 0.71. Our selected approach is able to outperform the baseline provided for the competition.
%R 10.18653/v1/2024.semeval-1.9
%U https://aclanthology.org/2024.semeval-1.9/
%U https://doi.org/10.18653/v1/2024.semeval-1.9
%P 53-59
Markdown (Informal)
[McRock at SemEval-2024 Task 4: Mistral 7B for Multilingual Detection of Persuasion Techniques In Memes](https://aclanthology.org/2024.semeval-1.9/) (Siino, SemEval 2024)
ACL