Reading Personality Preferences From Motion Patterns in Computer Mouse Operations
Reading Personality Preferences From Motion Patterns in Computer Mouse Operations
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DOI：
10.1109/taffc.2020.3023296
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发表时间：
2022-07
影响因子：
11.2
通讯作者：
Yinghui Zhao;D. Miao;Zhongmin Cai
中科院分区：
文献类型：
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作者：
Yinghui Zhao;D. Miao;Zhongmin Cai
人格不仅在人们的真实的生活中扮演着重要的角色，而且也成为各种在线服务的重要因素。传统的人格评估方法通常要求用户回答一长串问题，因此在许多在线系统中不实用。利用系统中一些普遍存在的数据进行人格评价是更可取的。本文报告了一项对照研究，探讨常见的鼠标操作作为一种潜在的新型数据源，在线人格评估。我们建立了一个精心制作的个性鼠标行为数据集，从146个主题，并提出运动学和调整功能来表征鼠标的运动模式。统计方法和机器学习算法，通过相关性分析，可信度分析和个性识别实验来研究个性偏好和鼠标运动特征之间的联系。结果揭示了一些有趣的表达的认知个性的观点反映在鼠标运动模式，如快速启动加速和更好的控制器。性能评估表明，它可以识别不同的个性偏好，使用鼠标运动特征的准确率从60.6%到78.3%。我们的研究结果表明，有可能使用鼠标操作行为作为一个新的数据源，在各种信息系统的人格评估。
Personality not only plays essential roles in people's real lives, but also becomes an important factor for various online services. Traditional approaches to personality assessment usually ask users to answer a long list of questions and are thus not practical in many online systems. It is more desirable to use some universally available data in the system to perform personality assessment. This article reports a controlled study to investigate common mouse operations as a potential new type of data source for online personality assessment. We establish an elaborate personality-mouse behavior dataset from 146 subjects and propose kinematic and adjustment features to characterize mouse motion patterns. Statistical approaches and machine learning algorithms are employed to examine the connections between personality preferences and mouse motion features via correlation analysis, discernibility analysis, and personality recognition experiments. The results reveal some interesting expressions of cognitive personality perspectives reflected in mouse motion patterns, such as fast starting acceleration and better controller. Performance evaluation shows it is possible to recognize different personality preferences using mouse motion features with accuracies ranging from 60.6 to 78.3 percent. Our findings suggest a potential to use mouse operational behaviors as a new data source for personality assessment in various information systems.