Prediction of USA November 2020 Election Results Using Multifactor Twitter Data Analysis Method
| Autor: | Sabuncu, Ibrahim, Balci, Mehmet Ali, Akguller, Omer |
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| Rok vydání: | 2020 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | In studies on election result prediction based on Twitter data, estimates were made using one of the factors such as the number of positive, negative, and neutral tweets posted about parties, the effect size of these tweets (the number of re-tweets), or the number of people who posted these tweets. However, no study was found that used all of these factors together. The goal of this study is to develop a new approach that takes into account all of the factors described and contributes to the literature in this context. A new multifactor model for the election result prediction based on Twitter data has been developed for this purpose. The model was tested by attempting to predict the results of the US 2020 elections in November, which had not yet taken place when the first version of this article was written. Also, a comparison has been made with alternative estimation approaches in the literature. Analyzes were made for approximately 10 million tweets collected between September 1 and October 21, 2020. As a result of the analysis, consistent with the results of the polls, Biden wins the election with a difference of 9.22% according to our method of estimating votes based on positive and negative tweet numbers, which are the current approaches in the literature. However, by using our multifactor model, the parameters for 3 November were calculated as -0.213423 for Democrats and 0.0455818 for Republicans. Based on these scores, it is concluded that the Republicans will win the election with a very small margin. Comment: 19 pages, 1 table, 4 figures. This is the second version of the article. We wanted to publish the results of the forecast analysis before the 3rd November elections. Follow for updates |
| Databáze: | arXiv |
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