Abstract
In the digital age, social media platforms serve as key venues for individuals to express opinions, emotions, and sentiments on various topics, from politics and social issues to products and services. This study explores sentiment analysis on social media data, utilizing natural language processing (NLP) techniques to decode public sentiment. The primary goal is to analyze sentiment in social media posts to gain insights into public opinion on specific topics. By applying NLP algorithms, text mining, and machine learning methodologies, we aim to extract meaningful patterns and sentiments from the vast textual data generated on social media.