Kaiser-Meyer-Olkin因子分析:基于随机森林分类器的手机游戏成瘾定量分析方法

Jefferson A. Costales, J. J. J. Catulay, Jeffrey Costales, Noel Bermudez
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引用次数: 4

摘要

在当今世界,技术使我们进步和创新,发展速度更快。我们利用科技从传统生活向数字化生活创新。有一些技术进步,比如手机游戏,是技术发展的结果。游戏是一种娱乐消遣,通过移动设备上的应用程序的形式变得可行。科技是有益的,但它也有负面影响:上瘾。这项研究的目的是了解学生玩手机游戏的时间和他们的社交活动之间是否存在联系。该研究还试图发现在手游成瘾中重要的不同特征,因为它们可以用来检测成瘾的早期迹象。对于重要性特征,研究人员采用了随机森林分类器。为了保证数据的充足性,本研究将采用因子分析和Kaiser-Meyer-Olkin方法。这些信息可以用来改进未来的研究。研究人员收集并使用了来自菲律宾几所大学的513名大学生的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Kaiser-Meyer-Olkin Factor Analysis: A Quantitative Approach on Mobile Gaming Addiction using Random Forest Classifier
Technology allows us to progress and innovate in today's world, which advances at a faster pace. We innovate from traditional to digital life with the use of technology. There have been several technological advances, such as Mobile Gaming, that have occurred as a result of the evolution of technology. Gaming is a recreational pastime that has become available through technology in the form of apps for mobile devices. Technology is beneficial, but it also has a negative side effect: addiction. The goal of the study is to see if there is any link between a student's time spent playing mobile games and their social interactions. The study also attempts to discover different features that are important in mobile gaming addiction since they can be used to detect early signs of addiction. For the feature of importance, the researchers applied Random Forest Classifier. To ensure that the data is adequate, the study will employ factor analysis and Kaiser-Meyer-Olkin. This information can be utilized to improve the future study. The researchers gathered and used data from 513 college students from several Philippine universities.
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