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Conference Papers Year : 2017

Forecasting the 2016 US Presidential Elections Using Sentiment Analysis

Prabhsimran Singh
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Ravinder Singh Sawhney
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Karanjeet Singh Kahlon
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  • PersonId : 1030988

Abstract

The aim of this paper is to make a zealous effort towards true prediction of the 2016 US Presidential Elections. We propose a novel technique to predict the outcome of US presidential elections using sentiment analysis. For this data was collected from a famous social networking website (SNW) Twitter in form of tweets within a period starting from September 1, 2016 to October 31, 2016. To accomplish this mammoth task of prediction, we build a model in WEKA 3.8 using support vector machine which is a supervised machine learning algorithm. Our results showed that Donald Trump was likely to emerge winner of 2016 US Presidential Elections.
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hal-01768531 , version 1 (17-04-2018)

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Prabhsimran Singh, Ravinder Singh Sawhney, Karanjeet Singh Kahlon. Forecasting the 2016 US Presidential Elections Using Sentiment Analysis. 16th Conference on e-Business, e-Services and e-Society (I3E), Nov 2017, Delhi, India. pp.412-423, ⟨10.1007/978-3-319-68557-1_36⟩. ⟨hal-01768531⟩
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