<b>Research data for the study "</b><b>Predicting Behavior Patterns in Online and PDF Magazines with AI Eye Tracking"</b>

The scope of the research was to understand how reliable AI Eye tracking is in predicting how online content affects readers' attention patterns. This analysis is part of the study entitled: "Predicting Behavior Patterns in Online and PDF Magazines with AI Eye Tracking." For this research, we used neuromarketing eye-tracking AI prediction software (Predict) built on one of the world's largest consumer neuroscience databases (n=180,000) with eye-tracking database participants globally, with 100bn+ data points within 15 consumer contexts. The magazines we tested were 'Hybrid,’ written by students from Oxford Brooke University, 'Oxford Students,’ by students from Oxford University, and 'Oxconnect,’ by students from Oxford Business College.本研究旨在探究人工智能眼动追踪（AI Eye Tracking）技术在预测网络内容对读者注意力模式影响方面的可靠性。本分析隶属于题为《基于人工智能眼动追踪技术预测在线与PDF杂志中的行为模式》的研究课题。本次研究采用的神经营销（neuromarketing）眼动追踪AI预测软件（Predict），依托全球规模最大的消费者神经科学数据库之一（样本量n=180,000）构建，该数据库收录了全球眼动追踪数据库参与者的相关数据，在15个消费场景下累计拥有超1000亿个数据点。本次测试的杂志包括：由牛津布鲁克斯大学学生创作的《Hybrid》、牛津大学学生创作的《Oxford Students》，以及牛津商学院学生创作的《Oxconnect》。