Visual Sentiment Analysis: A Natural DisasterUse-case Task at MediaEval 2021

TL;DR

This paper introduces the first MediaEval Visual Sentiment Analysis task focused on predicting emotional responses to natural disaster images shared on social media, highlighting its societal importance and research potential.

Contribution

It presents a new benchmark dataset and evaluation metrics for analyzing emotional responses to disaster-related images, fostering research in this important application area.

Findings

Dataset and metrics for disaster image sentiment analysis

Three sub-tasks exploring different aspects of the challenge

Potential for societal impact and future research directions

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.