Please use this identifier to cite or link to this item: 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
Twitter
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

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