In recent years, social media has emerged as a powerful tool for understanding public opinions and sentiments. This book explores the application of social media data analysis to study people's sentiment towards water resources. Using R software and text mining techniques, the authors analyze a dataset collected from Twitter, classifying tweets into positive, negative, and neutral sentiments. The analysis includes data collection, processing, sentiment classification, and visualization. By observing the most frequent words, geographic distribution, and implementing word network analysis, the study uncovers valuable insights on environmental discussions and challenges related to water resources.