A Systematic Review of Predecting Elections based on Social Media Data

In the dynamic landscape of modern politics, comprehending the sentiments of voters has emerged as a pivotal element for effective campaigning and policy formulation. This abstract encapsulates an in-depth exploration of election sentiment analysis, employing cutting-edge data analytics methodologies to unravel the multifaceted dimensions of voter perspectives. Leveraging the power of natural language processing, sentiment analysis, and machine learning algorithms, this study endeavours to decode sentiments expressed across diverse platforms, offering profound insights into the intricate tapestry of voter behaviours, preferences, and concerns. Through meticulous scrutiny of textual data extracted from sprawling social media platforms, this research enriches the discourse surrounding electoral dynamics. By facilitating a granular understanding of sentiment patterns, it equips political stakeholders with invaluable tools to craft astute strategies and cultivate a nuanced comprehension of democratic processes.