International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 17, No. 4, 8 Aug. 2025
Cover page and Table of Contents: PDF (size: 430KB)
Video Game Sales Prediction Based on Social Media Data Using Machine Learning: A Survey and Future Directions
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Author(s)
Oleg Chertov
1
Valerii Buslaiev
1,*
Index Terms
Social Media Analytics, Sentiment Analysis, Video Games, Sales Prediction, NLP, Consumer Behavior, Predictive Analytics, Machine Learning
Abstract
The rapid growth of the video game industry and its reliance on digital distribution have created new opportunities for data-driven sales forecasting. Social media platforms serve as influential environments where consumer sentiment, trends, and discussions impact purchasing behaviors. This study examines the potential of using sentiment analysis of social media data to predict video game sales. While traditional sales forecasting models mainly depend on historical sales data and statistical techniques, sentiment analysis offers real-time insights into consumer interest and market demand. This paper reviews existing research on video game sales prediction, the application of sentiment analysis in the gaming industry, and sentiment-based forecasting models in other domains. The findings highlight a significant research gap in applying sentiment analysis to video game sales forecasting, despite its demonstrated efficacy in related fields. The study emphasizes the advantages and challenges of integrating sentiment analysis with traditional forecasting methods and proposes future research directions to enhance predictive accuracy.
Cite This Paper
Oleg Chertov, Valerii Buslaiev, "Video Game Sales Prediction Based on Social Media Data Using Machine Learning: A Survey and Future Directions", International Journal of Information Technology and Computer Science(IJITCS), Vol.17, No.4, pp.49-57, 2025. DOI:10.5815/ijitcs.2025.04.05
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