This paper presents an overview of the ImageArg shared task, the first multimodal Argument Mining shared task co-located with the 10th Workshop on Argument Mining at EMNLP 2023. The shared task comprises two classification subtasks - (1) Subtask-A: Argument Stance Classification; (2) Subtask-B: Image Persuasiveness Classification. The former determines the stance of a tweet containing an image and a piece of text toward a controversial topic (e.g., gun control and abortion). The latter determines whether the image makes the tweet text more persuasive. The shared task received 31 submissions for Subtask-A and 21 submissions for Subtask-B from 9 different teams across 6 countries. The top submission in Subtask-A achieved an F1-score of 0.8647 while the best submission in Subtask-B achieved an F1-score of 0.5561.

翻译：本文介绍了ImageArg共享任务的总体情况，这是与EMNLP 2023第十届论辩挖掘研讨会联合主办的首届多模态论辩挖掘共享任务。该共享任务包含两个分类子任务：（1）子任务A：论辩立场分类；（2）子任务B：图像说服力分类。前者用于判定包含图像和文本的推文对有争议话题（如枪支管控和堕胎）所持的立场，后者则用于判定图像是否增强了推文文本的说服力。该共享任务共收到来自6个国家9个团队的31份子任务A提交材料和21份子任务B提交材料。子任务A的最佳提交方案取得了0.8647的F1值，而子任务B的最佳方案取得了0.5561的F1值。