Sentiment Analysis from Images of Natural Disasters

TL;DR

This paper explores how analyzing emotions and opinions in disaster-related images on social media can enhance information extraction for end-users, addressing challenges and proposing benchmarks for future research.

Contribution

It introduces a focus on visual sentiment analysis in disaster images, highlighting its potential to improve social media data interpretation and setting directions for future benchmarks.

Findings

Visual sentiment analysis can improve disaster information extraction

Identifies key challenges in analyzing disaster-related images

Proposes benchmarks for future research in visual sentiment analysis

Abstract

Social media have been widely exploited to detect and gather relevant information about opinions and events. However, the relevance of the information is very subjective and rather depends on the application and the end-users. In this article, we tackle a specific facet of social media data processing, namely the sentiment analysis of disaster-related images by considering people's opinions, attitudes, feelings and emotions. We analyze how visual sentiment analysis can improve the results for the end-users/beneficiaries in terms of mining information from social media. We also identify the challenges and related applications, which could help defining a benchmark for future research efforts in visual sentiment analysis.