Soelistio, Yustinus Eko and Tunggawan, Elvyna (2016) And the winner is …: Bayesian Twitter-based prediction on 2016 U.S. presidential election. In: : 2016 International Conference on Computer, Control, Informatics and its Applications (IC3INA), 3-5 Oct. 2016, Tangerang.
Full text not available from this repository.Abstract
This paper describes a Naive Bayesian predictive model for 2016 U.S. Presidential Election based on Twitter data. We use 33,708 tweets gathered since December 16, 2015 until February 29, 2016. We propose a simple way for data preprocessing which can still achieve 95.8% accuracy on predicting sentiments. The predicted sentiments are used to forecast the U.S. Republican and Democratic parties candidacies. The forecast is compared to the poll collected from RealClearPolitics.com with 26.7% accuracy. However, the true forecasting capacity of the method still have to be observed after the election process come to conclusion.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 004 Computer Science, Data Processing, Hardware |
| Divisions: | Faculty of Engineering & Informatics > Information System |
| Depositing User: | Administrator UMN Library |
| Date Deposited: | 14 Dec 2021 08:01 |
| Last Modified: | 14 Dec 2021 08:01 |
| URI: | https://kc.umn.ac.id/id/eprint/19645 |
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