Climate Change and Natural Disasters: A Proposal for Sentiment Analysis on Social Media

• Lucas Lammel IFRS
• Andrws Aires Vieira IFRS

DOI: https://doi.org/10.5753/erbd.2025.6692

Abstract

Climate change represents one of the greatest global challenges, with broad and varied impacts. With the abundance of information shared on social media, these platforms become rich sources for sentiment analysis on the topic. This study proposes a methodology using Natural Language Processing techniques to analyze emotions expressed in posts related to climate change and natural disasters. The approach combines lexical-based methods, machine learning and deep learning models to provide a robust framework for understanding public sentiment.

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