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

  • Zhaomin Xiao
  • , Eduardo Blanco

Research output: Contribution to journalConference articlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)2561-2571
Number of pages11
JournalProceedings - International Conference on Computational Linguistics, COLING
Volume29
Issue number1
StatePublished - 2022
Externally publishedYes
Event29th International Conference on Computational Linguistics, COLING 2022 - Gyeongju, Korea, Republic of
Duration: Oct 12 2022Oct 17 2022

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Theoretical Computer Science

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