GitHub - sqiprasanna/climate_change_tweets_sentiment_analysis

Briefly describe the project you worked on. What did you create, who did you create it for, and how did you approach this project?

In the climate sentiment analysis project, I developed a system to analyze the sentiment of Twitter users towards climate change. The project involved working with quality data and CrowdFlower judgments. I addressed the dataset imbalance by performing random under-sampling and SMOTE sampling. I evaluated various classification models based on precision, recall, and F1-score, with Random Forest performing the best at 92% F1-score. I implemented a web interface using Flask that ran on the best model (Random Forest) and applied it to scrape tweets from 2022. The analysis revealed a significant number of tweets denying climate change. This project showcases my expertise in sentiment analysis, data preprocessing, classification modeling, and web application development.