@inproceedings{khurshid-das-2024-magnum,
    title = "Magnum {JUCSE} at {S}em{E}val-2024 Task 4: Multilingual Detection of Persuasion Techniques in Memes",
    author = "Khurshid, Adnan  and
      Das, Dipankar",
    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://preview.aclanthology.org/jlcl-multiple-ingestion/2024.semeval-1.146/",
    doi = "10.18653/v1/2024.semeval-1.146",
    pages = "1015--1018",
    abstract = "This paper focuses on the task of detecting persuasion techniques organised in a hierarchy within meme text in multiple languages like English, North Macedonian, Arabic and Bulgarian, exploring the ways in which textual elements contribute to the dissemination of persuasive messages.The main strategy of the system is to train a binary classifier for each node in the hierarchy and predict labels in a top down fashion by seeing the confidence value of the prediction at any node. For each unique label in the hierarchy, a dataset is created from the original dataset which is then used to train the binary classifier for that label"
}