Sentiment Analysis on Climate Change: An empirical approach

Sentiment Analysis (SA) is a Natural Language Processing (NLP) based approach to systematically classify and extract subjective information in social media and other sources. This method helps business and other domains to understand the sentiment / opinion about the product, service, an individual or brand by monitoring online conversations. Climate change is a critical issue of our time. From fluctuating weather conditions that lurk food generation, to increasing sea levels that upsurge the threat of shattering flooding. The results of climate change are universal in scope and never-before in scale. The recent advance in deep learning has the ability of applying contemporary algorithms to analyze text and the performance has improved significantly. In this article, a novel approach for analyzing people’s sentiment about climate change on Twitter Data is explored using deep learning methods. Experiment evaluation shows that the proposed method outperforms the state-of-the-art approaches.