A Comprehensive Review of Social Media Data in Election Prediction

A Comprehensive Review of Social Media Data in Election Prediction

1Jami Kavitha, 2A. Sravya, 3Ch. Likhitha, 4M. V. V. Sai Kumar, 5P. Meghan Sai.

1Assistant Professor, 2Student, 3Student, 4Student, 5Student

1Computer Science and Engineering,

1Sanketika Vidya Parishad Engineering College, Visakhapatnam, INDIA

Abstract

This project focuses on building a sentiment analysis system to aid in election prediction by analysing tweets related to political leaders. It leverages machine learning, specifically the Passive Aggressive Classifier, and incorporates text preprocessing techniques such as TF-IDF vectorization to classify tweets as either positive or negative. A user-friendly Flask web application is developed, allowing users to upload CSV files containing tweets. The application processes the data and displays the sentiment distribution through a pie chart visualization. By capturing public sentiment on social media, the system offers valuable insights that can contribute to forecasting election outcomes.

Keywords: Sentiment Analysis, Election Prediction, Tweet Classification, Passive Aggressive Classifier