Predicting Elections With Social Media And ML
Keywords:
Sentiment Analysis, Bidirectional Recurrent Neural Network Model, Neural Architectures, Social media (SM)Abstract
Millions of people are expected to participate in
the greatest democratic exercise in human
history—the general election in India. One of
the most widely utilized social media sites for
sharing opinions on subjects like politics, sports,
and entertainment is Twitter. One of the most
important channels for politicians and political
parties to advertise themselves in the run-up to
elections is social media. The aim of this paper
is to do sentiment analysis of the Social Media
network in the months leading up to the election
and build a model that will be able to interpret
the political subject matter. The analysis will be
based on the politicians and the parties involved
in the elections. This analysis can be used to
acquire knowledge of the sentiments involved in
the elections and predict the outcome of the
upcoming elections. The models built are a
Bidirectional Recurrent Neural Network model.
The model is optimized using varying neural
architectures and hyper parameter tuning.
Kernel Regularization methods are used to
address over fitting to get the best performance.
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