一个互动和情绪的数据集,用于网站用户体验评估和评估
Andrea Esposito1, Giuseppe Desolda2, Rosa Lanzilotti2
1Department of Computer Science, University of Bari Aldo Moro, Via E. Orabona 4, 70125, Bari, Italy. andrea.esposito@uniba.it.
Scientific data
|November 17, 2025
概括
这个数据集捕捉了用户网站的交互和情绪,使人工智能能够从鼠标移动和按键按中检测情绪. 这项研究推进了情感计算,以改善用户体验 (UX) 和个性化的网络内容.
科学领域:
- 情感计算是一种情感计算.
- 人与计算机的交互 (HCI)
- 数据科学数据科学数据科学
背景情况:
- 了解用户的情绪对于改善数字体验至关重要.
- 现有的情绪检测方法通常依赖于明确的用户反.
- 需要数据集,将隐含的用户行为与情绪状态联系起来.
研究的目的:
- 引入一种用于情感计算研究的新型数据集.
- 促进基于交互数据的情感检测AI系统的开发.
- 为了能够对用户情绪和网站交互之间的相互作用进行细微分析.
主要方法:
- 从各种网站收集了30天的用户交互日志 (鼠标移动,按键).
- 将交互数据与相应的情感数据配对,使用Ekman的情感模型进行编码.
- 结构化数据用于分析人机交互和情感计算.
主要成果:
- 该数据集为研究网络导航期间的情绪反应提供了丰富的资源.
- 能够分析特定的交互模式和情绪状态之间的相关性.
- 为训练人工智能模型从隐性用户行为推断情绪提供了基础.
结论:
- 该数据集支持在HCI中推进AI驱动的情感识别.
- 它可以带来更适应和个性化的用户体验.
- 有助于研究情绪如何影响网站上的用户行为.
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