Football Match Result Prediction using Twitter Statistical/Historical Data

Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/4137

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DC Field	Value	Language
dc.contributor.author	Jangir, Dipesh	-
dc.contributor.author	Hota, Lopamudra	-
dc.contributor.author	Nayak, Biraja Prasad	-
dc.contributor.author	Kumar, Arun	-
dc.date.accessioned	2023-12-18T04:44:08Z	-
dc.date.available	2023-12-18T04:44:08Z	-
dc.date.issued	2023-12	-
dc.identifier.citation	5th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR), NIT Kurukshetra, 07-09 December 2023	en_US
dc.identifier.uri	http://hdl.handle.net/2080/4137	-
dc.description	Copyright belongs to proceeding publisher	en_US
dc.description.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	en_US
dc.subject	Football Match	en_US
dc.subject	Result Prediction	en_US
dc.subject	Twitter	en_US
dc.subject	Statistical	en_US
dc.subject	A Random Forest	en_US
dc.subject	SVM	en_US
dc.subject	Naive Bayes	en_US
dc.subject	KNN	en_US
dc.title	Football Match Result Prediction using Twitter Statistical/Historical Data	en_US
dc.type	Article	en_US
Appears in Collections:	Conference Papers

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