Anzeige
Erschienen in:
2020 | OriginalPaper | Buchkapitel
Bayesian Prediction on PM Modi’s Future in 2019
verfasst von : Aniruddh Sanga, Ashirwad Samuel, Nidhi Rathaur, Pelumi Abimbola, Sakshi Babbar
Erschienen in: Proceedings of ICRIC 2019
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Abstract
Electing a Prime Minister (PM) is a process that occurs every 5 years in India, through conducting an election. Who will win the election is one of the most asked questions on everyone’s tongue, as the election is just few months away. The objective of this research is to predict the likelihood of PM Narendra Modi’s chances to continue as the Prime Minister of India using Bayesian network approach. The aim of this research is not to develop a new predictive algorithm, but to use the existing approach for making predictions on a real-life scenario. Our Bayesian modeling is based on public responses available on social media, India statistics, and news articles on the key policies undertaken by PM Narendra Modi during his current tenure. We explore using causal and diagnostic reasoning to find new insights on the factors shaping his win or no-win, verdict on his government strength and weakness. Our Bayesian model reveals that the current Prime Minister Modi has 61.4% chances of winning the upcoming 2019 elections.