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Current news datasets merely focus on text features on the news and rarelyleverage the feature of images, excluding numerous essential features for newsclassification. In this paper, we propose a new dataset, N24News, which isgenerated from New York Times with 24 categories and contains both text andimage information in each news. We use a multitask multimodal method and theexperimental results show multimodal news classification performs better thantext-only news classification. Depending on the length of the text, theclassification accuracy can be increased by up to 8.11%. Our research revealsthe relationship between the performance of a multimodal classifier and itssub-classifiers, and also the possible improvements when applying multimodal innews classification. N24News is shown to have great potential to prompt themultimodal news studies.

N24News: A New Dataset for Multimodal News Classification