Prediction of the General Election 2024 Result in Pakistan: Using Markov Chain - Asma Zaffar; Ovais Siraj Siddiqui; Hina Zafar (Journal of Management Practices, Humanities and Social Sciences, 2023)
The election is an event where all the political parties and factions and their Leaders are projected to participate. Predicting election outcomes is complicated, encompassing different factors that influence voter conduct and political dynamics. This study introduces a novel approach to predict the outcomes of the 2024 general election in Pakistan by employing Markov chain analysis. The abstract highlights the methodology, theoretical foundations, practical implications, and potential future research directions. The paper discusses the theoretical foundations of Markov chain theory as applied to electoral systems, emphasizing state transitions, steady-state distributions, and electoral process periodicity. The study's predictions offer valuable insights for political parties, policymakers, and the public in making informed decisions. The methodology can be adapted for future elections, contributing to data-driven political strategies. It is advisable to rent a couple of forecasting strategies, incorporate extra statistics assets, which include polling records and professional critiques, and analyze the consequences within the broader context of political dynamics in Pakistan. This study shows that PTI has a bright chance to win the election 2024.