Reducing Social Media Users’ Biases to Predict the Outcome of Australian Federal Election 2019

Abstract

Several online social networking sites (OSNs) are being used as a medium of expressing any ideas, opinions, thoughts towards any regular or special issues and also for support or even oppose any social or political matters at the same time. At the age of this modern technology, in any country, people would like to post their views regarding any political party during the election period on such emerging OSNs in order to demonstrate their stands upon them. In this paper, we incorporated the tweets relevant to the Australian federal Election 2019, with a view to serve our primary purpose of predicting the outcome of it. We aggregated two efficacious techniques to extract the information from a large Twitter dataset to count a virtual support for each corresponding political group and propose an approach of reducing users’ biases in OSNs to predict outcome of the election more efficiently. Our investigation finds close relevance with the original results of the election published by the Australian Electoral Commission.