Deep learning-based election results prediction using Twitter activity

Haider Ali,Shabana Habib,Haleem Farman,Adel Ammar,Zahid Khan,Hikmat Yar

doi:10.1007/s00500-021-06569-5

Haider Ali, Shabana Habib + Show 4 more

Open Access

https://doi.org/10.1007/s00500-021-06569-5

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Abstract

Nowadays, political parties have widely adopted social media for their party promotions and election campaigns. During the election, Twitter and other social media platforms are used for political coverage to promote the party and its candidates. This research discusses and estimates the stability of many volumetric social media approaches to forecast election results from social media activities. Numerous machine learning approaches are applied to opinions shared on social media for predicting election results. This paper presents a machine learning model based on sentiment analysis to predict Pakistan's general election results. In a general election, voters vote for their favorite party or candidate based on their personal interests. Social media has been extensively used for the campaign in Pakistan general election 2018. Using a machine learning technique, we provide a five-step process to analyze the overall election results, whether fair or unfair. The work is concluded with detailed experimental results along with discussion on the outcomes of sentiment analysis for real-world forecasting and approval of general elections in Pakistan.

Highlights

The widespread use of the social media network for communication, social participation, and self-expression has resulted in many individual data being willingly disclosed online
This paper presents a machine learning model based on sentiment analysis to predict Pakistan's general election results
RapidMiner uses as a simulation tool that has pre-defined operators and classifiers

Summary

Introduction

The widespread use of the social media network for communication, social participation, and self-expression has resulted in many individual data being willingly disclosed online. Computer technology-based social media platforms have benefited people for self-expression, communication, and social participation These social media sources are responsible for sharing text, audio, and video links between individuals worldwide to be well informed and keeping in touch with others. This explosive social development can be seen on Facebook, Linked In, Friend Feed, Myspace, and many more, but the flow of Twitter is much more than other platforms [2]. Many people have been attracted by social media platforms such as Instagram, Twitter, and Facebook, which allow them to express their thoughts, feelings, and ideas about various people, places, and things People give their views on these social websites for the political party election campaign. The social media platform was less useful for Baluchistan

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