Information Technology: Faculty Publications
Sales Predictions for Video Games Using Predictive Analytics of Market Data
Document Type
Conference Proceeding
Publication Date
1-27-2024
Publication Title
IEEE 16th International Conference on Communication Systems and Network Technologies Proceedings
DOI
10.1109/CICN63059.2024.10847429
ISBN
9798331505264
Abstract
The advancements and sales of technology have changed drastically within the last twenty years, affecting the sales of video games as their platforms and content have been able to change alongside technological advances. Predictive analytics helps those in the video game industry to keep up with these constant changes when considering factors such as sales. This study considers the need and application of predictive analytics using the classification models linear regression and decision trees to predict future sales performance. We conduct this research to prove the benefits of using predictive analytics to predict future sales performance on data for video games.
Recommended Citation
Gray, Dashae, Atef Mohamed Shalan, Christopher Kadlec.
2024.
"Sales Predictions for Video Games Using Predictive Analytics of Market Data."
IEEE 16th International Conference on Communication Systems and Network Technologies Proceedings: 1510-1516: Institute of Electrical and Electronics Engineers Inc..
doi: 10.1109/CICN63059.2024.10847429 isbn: 9798331505264
https://digitalcommons.georgiasouthern.edu/information-tech-facpubs/194
Copyright
See the publisher's copyright and reuse policies.
Comments
Georgia Southern University faculty members, Atef Mohamed Shalan and Christopher Kadlec co-authored "Sales Predictions for Video Games Using Predictive Analytics of Market Data".