With the rising need to address shifting global temperatures, precipitation patterns, and atmospheric conditions, text mining and sentiment analysis play a crucial role in managing climate change and promoting environmental sustainability. These techniques provide valuable insights to support decision-making, stakeholder engagement, risk management, policymaking, and corporate communication efforts to address the changing climate and respond to important crises. Further research into text mining and sentiment analysis is necessary to understand the public's perception on climate change, address corporate concerns, and identify emerging risks associated with the environment. Text Mining and Sentiment Analysis in Climate Change and Environmental Sustainability provides updated information on the emergence and role of text mining and sentiment analysis in predicting climate change and promoting environmental sustainability. It covers emerging trends involved in the nexus of text mining, sentiment analysis, climate change and environmental sustainability. This book covers topics such as environmental science, sustainable development, and machine learning, and is a useful resource for climatologists, environmental scientists, computer engineers, data scientists, academicians, and researchers.
