Analysis of the Impact of Other Factors on the Download Volume of New Games Using a Polynomial Model: Taking the Top 50 Popular New Games as an Example

With the advent of the internet era, the gaming industry has flourished, bringing many opportunities for game developers. Entertainment is a necessary activity in people's lives, and as an activity with entertainment characteristics, games have become a way for people to spend their leisure time in the current era. Whether and how to release a new game is often a question that many manufacturers need to consider. For a new game, it has certain development costs and cycles. How to gain an advantage, we believe that the number of downloads is very important for the number of players and the game's revenue, so how to increase the number of downloads is a problem that needs to be solved. Moreover, the release of a new game often comes with risks and competition. The lag in information and the existence of information gaps often easily hinder the companies that release new games. To reduce the lag in information, we will use web crawlers to crawl real-time game data in this paper. At the same time, to analyze the correlation between data, we use regression analysis. We aim to improve the number of downloads and obtain a regression model with the number of downloads as the dependent variable and attention, anticipation, game memory size, forum post count, and game review count as independent variables. To facilitate the establishment of the model, we use y to represent the dependent variable and x1, x2, x3, x4, x5 to represent each independent variable. The final model is y = 8.287e+04 + 7.690e-08×1^2 + 2.007e-04×1x3 - 5.613e+01×5. This model can well reflect the correlation factors related to the number of downloads and also reflect the relationship between them. In the end, through this model, we conclude that for game companies, if they want to achieve a high number of downloads, they need to focus not only on increasing attention but also on improving the number of reviews. At the same time, they should also manage the forum well and strengthen the management of the quality of forum posts.

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Published
2024-10-18
DOI
https://doi.org/10.1109/icmlca63499.2024.10753972
Primary Topic
Digital Games and Media
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article
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article

Analysis of the Impact of Other Factors on the Download Volume of New Games Using a Polynomial Model: Taking the Top 50 Popular New Games as an Example

Peng Yuan, Ziqing Zhong
Digital Games and Media
article

Analysis of the Impact of Other Factors on the Download Volume of New Games Using a Polynomial Model: Taking the Top 50 Popular New Games as an Example

Peng Yuan, Ziqing Zhong
article en

Abstract

With the advent of the internet era, the gaming industry has flourished, bringing many opportunities for game developers. Entertainment is a necessary activity in people's lives, and as an activity with entertainment characteristics, games have become a way for people to spend their leisure time in the current era. Whether and how to release a new game is often a question that many manufacturers need to consider. For a new game, it has certain development costs and cycles. How to gain an advantage, we believe that the number of downloads is very important for the number of players and the game's revenue, so how to increase the number of downloads is a problem that needs to be solved. Moreover, the release of a new game often comes with risks and competition. The lag in information and the existence of information gaps often easily hinder the companies that release new games. To reduce the lag in information, we will use web crawlers to crawl real-time game data in this paper. At the same time, to analyze the correlation between data, we use regression analysis. We aim to improve the number of downloads and obtain a regression model with the number of downloads as the dependent variable and attention, anticipation, game memory size, forum post count, and game review count as independent variables. To facilitate the establishment of the model, we use y to represent the dependent variable and x1, x2, x3, x4, x5 to represent each independent variable. The final model is y = 8.287e+04 + 7.690e-08×1^2 + 2.007e-04×1x3 - 5.613e+01×5. This model can well reflect the correlation factors related to the number of downloads and also reflect the relationship between them. In the end, through this model, we conclude that for game companies, if they want to achieve a high number of downloads, they need to focus not only on increasing attention but also on improving the number of reviews. At the same time, they should also manage the forum well and strengthen the management of the quality of forum posts.

Beijing Institute of Technology (CN), Zhuhai Institute of Advanced Technology (CN)
Openalex Percentile: Top 67%
Digital Games and Media
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Analysis of the Impact of Other Factors on the Download Volume of New Games Using a Polynomial Model: Taking the Top 50 Popular New Games as an Example — Peng Yuan, Ziqing Zhong · (2024) | TGRS Research Map | TGRS