Does Optical Character Recognition and Caption Generation Improve Emotion Detection in Microblog Posts?
نویسنده
چکیده
Emotion recognition in microblogs like Twitter is the task of assigning an emotion to a post from a predefined set of labels. This is often performed based on the Tweet text. In this paper, we investigate wether information from attached images contributes to this classification task. We use o↵-the-shelf tools to extract a signal from an image. Firstly, with employ optical character recognition (OCR), to make embedded text accessable, and secondly, we use automatic caption generation to generalize over the content of the depiction. Our experiments show that using the caption only slightly improves performance and only for the emotions fear, anger, disgust and trust. OCR shows a significant impact for joy, love, sadness, fear, and anger.
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