Authors of posts in social media communicate their emotions and what causes them with text and images. While there is work on emotion and stimulus detection for each modality separately, it is yet unknown if the modalities contain complementary emotion information in social media. We aim at filling this research gap and contribute a novel, annotated corpus of English multimodal Reddit posts. On this resource, we develop models to automatically detect the relation between image and text, an emotion stimulus category and the emotion class. We evaluate if these tasks require both modalities and find for the image-text relations, that text alone is sufficient for most categories (complementary, illustrative, opposing): the information in the text allows to predict if an image is required for emotion understanding. The emotions of anger and sadness are best predicted with a multimodal model, while text alone is sufficient for disgust, joy, and surprise. Stimuli depicted by objects, animals, food, or a person are best predicted by image-only models, while multimodal models are most effective on art, events, memes, places, or screenshots.

本文提供具有新颖性的英文 Reddit 帖子语料库，研究多模式社交媒体上图文情感信息的互补性，发现对于某些情感信息如愤怒和悲伤，多模式模型可以更好地预测；而对于某些信息如恶心、喜悦和惊讶，仅以文本信息便足够预测。

社交媒体上图像和文字表达情感的互补性