N24News: A New Dataset for Multimodal News Classification
Zhen Wang, Shan Xu, Xiangxie Zhang, Jie Yang · 2022
Current news datasets merely focus on text features on the news and rarely leverage the feature of images, excluding numerous essential features for news classification.In this paper, we propose a new dataset, N24News, which is generated from New York Times with 24 categories and contains both text and image information in each news.We use a multitask multimodal method and the experimental results show multimodal news classification performs better than text-only news classification.Depending on the length of the text, the classification accuracy can be increased by up to 8.11%.Our research reveals the relationship between the performance of a multimodal classifier and its sub-classifiers, and also the possible improvements when applying multimodal in news classification.N24News is shown to have great potential to prompt the multimodal news studies.