Mapping Sentiment: A Geospatial Analysis of Twitter Data in Indian Premier League 2023

This paper presents application of machine learning and geospatial analysis to examine sentiments from Twitter data during the 2023 season of the Indian Premier League (IPL). Utilizing machine learning models (linear SVM and logistic regression), we effectively categorized sentiments into negative, neutral, and positive classes, attaining impressive overall accuracy of 96.8% and 97.1%, respectively. The geospatial analysis led to map sentiment across various geographical locations in India, reflecting diverse public sentiment throughout the IPL season. We noticed intriguing temporal and spatial variations in sentiment distribution across March, April, and May in 2023, visually represented via a heatmap. This comprehensive examination of sentiment distribution, linked to a significant event like the IPL, opens new horizons for understanding public perception and emotional response to large-scale sporting events.