Twitter Data ETL for Sentiment Analysis

• Tech Stack: Python, HTML, CSS, Apache Airflow, AWS (EC2, S3)

- Created a web‑based application to provide the user with a detailed analysis of the sentiment of users on top 10 trending movies and songs.

- Scheduled a routine to fetch 1000 tweets at a time from Twitter; reducing overall response time by 50%; stored data in AWS S3 table for efficiently displaying data.

- Tested the scalability of web application by generating 10000 user requests using Apache Beam.