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Are People Located in the Places They Mention in Their Tweets? A Multimodal Approach

2022-10-01COLING 2022Code Available0· sign in to hype

Zhaomin Xiao, Eduardo Blanco

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Abstract

This paper introduces the problem of determining whether people are located in the places they mention in their tweets. In particular, we investigate the role of text and images to solve this challenging problem. We present a new corpus of tweets that contain both text and images. Our analyses show that this problem is multimodal at its core: human judgments depend on whether annotators have access to the text, the image, or both. Experimental results show that a neural architecture that combines both modalities yields better results. We also conduct an error analysis to provide insights into why and when each modality is beneficial.

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