Sentiment analysis of social media posts on mass deportation policies is important in order to assess the reactions of the common public toward such policy adaptations. In this paper, we conduct the aforementioned analysis on Reddit comments using text mining techniques. Positive, negative, and neutral sentiments are the three categories into which public responses are divided. The study entails cleaning the raw text data, using NLP tools, namely TextBlob and LLaMA3.2 ZeroShotOllamaClassifier to perform sentiment analysis and comparing the outcomes to derive valuable insights. Observations show that user karma and awards have an impact on public opinion variations. The results help to understand trends in online discourse through the use of natural language processing and data mining techniques.