SENTIMENT ANALYSIS ON SOCIAL MEDIA FOR POLITICAL FORECASTING: A COMPUTATIONAL SOCIAL SCIENCE APPROACH

Abstract

The use of sentiment analysis for political forecasting has gained traction as social media has become an essential platform for political discourse. This paper investigates the role of sentiment analysis in predicting political outcomes through the analysis of social media data. By employing computational techniques and natural language processing (NLP), this study assesses the sentiment of political discussions on platforms like Twitter, Facebook, and other social media channels. The findings reveal a significant correlation between public sentiment expressed online and election results, highlighting the potential of social media data as an indicator for political forecasting. This paper provides a comprehensive methodology for sentiment analysis, explores its applications in political science, and discusses its implications for future electoral predictions.