<p>In democratic systems, elections represent a recurring phenomenon. The prediction of electoral outcomes and the analysis of factors influencing the success of candidates and political parties constitute a dynamic and challenging area of research, engaging diverse stakeholders, including citizens, candidates, political parties, research institutions (public and private), and civil society organizations. With advancements in digital communication technologies, information-sharing tools, and social media platforms, the processes and dynamics of elections have undergone significant transformations. These changes have introduced greater complexity to the electoral system, driven by technologically empowered citizens, rapid dissemination of information, susceptibility to misinformation, and the proliferation of fake news and hate speech. Political parties and candidates increasingly leverage social media platforms such as Facebook, Twitter, YouTube, and Instagram to disseminate their manifestos, shape public opinion in their favour or against opponents, and engage voters. These efforts often involve substantial financial investments and human resources to influence electoral outcomes. This study aims to examine and predict electoral results at the micro-constituency level based on posts and interactions on social media platforms. It explores the role of IT cells in shaping voter opinions, the influence of hate speech on electoral processes, and the quantifiable engagement of voters from diverse geographic regions in ideological discourse on social media. By employing advanced data analytics, the study seeks to understand the multidimensional impact of these factors on voter behaviour and election outcomes. The predicted results are compared against actual electoral outcomes at the micro-constituency level to evaluate the predictive model’s limitations and identify areas for further refinement.</p>