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Visual Sentiment Analysis: A Natural DisasterUse-case Task at MediaEval 2021 (2111.11471v1)

Published 22 Nov 2021 in cs.CL

Abstract: The Visual Sentiment Analysis task is being offered for the first time at MediaEval. The main purpose of the task is to predict the emotional response to images of natural disasters shared on social media. Disaster-related images are generally complex and often evoke an emotional response, making them an ideal use case of visual sentiment analysis. We believe being able to perform meaningful analysis of natural disaster-related data could be of great societal importance, and a joint effort in this regard can open several interesting directions for future research. The task is composed of three sub-tasks, each aiming to explore a different aspect of the challenge. In this paper, we provide a detailed overview of the task, the general motivation of the task, and an overview of the dataset and the metrics to be used for the evaluation of the proposed solutions.

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Authors (7)
  1. Syed Zohaib Hassan (4 papers)
  2. Kashif Ahmad (36 papers)
  3. Michael A. Riegler (60 papers)
  4. Steven Hicks (9 papers)
  5. Nicola Conci (15 papers)
  6. Paal Halvorsen (4 papers)
  7. Ala Al-Fuqaha (82 papers)
Citations (7)

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