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http://hdl.handle.net/2080/4137| Title: | Football Match Result Prediction using Twitter Statistical/Historical Data |
| Authors: | Jangir, Dipesh Hota, Lopamudra Nayak, Biraja Prasad Kumar, Arun |
| Keywords: | Football Match Result Prediction Statistical A Random Forest SVM Naive Bayes KNN |
| Issue Date: | Dec-2023 |
| Citation: | 5th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR), NIT Kurukshetra, 07-09 December 2023 |
| Abstract: | The results of a football game provide a fascinating test because football is one of the most popular and widely played games. Forecasting can also assist clubs and administrators in making the right decisions to win associations and competitions. Many studies have been conducted on football match prediction using statistical or historical data and various models for prediction. However, in this paper, historical data and Twitter data were extracted from tweets related to the premier league season 2021/22. Various classification models are employed, including Random Forest, SVM, Na¨ıve Bayes, and KNN algorithm to see the outcomes of these models and their accuracy based on historical and Twitter datasets |
| Description: | Copyright belongs to proceeding publisher |
| URI: | http://hdl.handle.net/2080/4137 |
| Appears in Collections: | Conference Papers |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2023_ICDLAIR_DJnagir_Football.pdf | 698.8 kB | Adobe PDF | View/Open |
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