Abstract
For any topic in which the public opinion matters, there is a potential of using social media to evaluate the public opinion. Previous researches have proven the effectiveness of using social media as an indicator to elections. Nevertheless, the composition of social media users can never be the same as the real demographic. What makes things worse is the existence of malicious users who intend to manipulate the public’s tendencies toward candidates or parties. In this paper, we aim to increase the prediction correctness under the premise that the extracted data are noisy. By taking an individual’s trustworthiness, participation bias and the influence into account, we propose a novel method to forecast the U.S. presidential election in 2016 post facto and make predictions for the 2020 election. In essence, we identify the social media as a polling mechanism: What does social media predict as an election outcome?
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Huang, TC., Zaeem, R.N., Barber, K.S. (2022). Finding Trustworthy Users: Twitter Sentiment Towards US Presidential Candidates in 2016 and 2020. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2021. Lecture Notes in Networks and Systems, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-82196-8_59
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DOI: https://doi.org/10.1007/978-3-030-82196-8_59
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