CAREER: Human Behavior Assessment from Internet Usage: Foundations, Applications and Algorithms

人类与计算机，特别是与互联网的互动正在不断增加。因此，研究使用计算机的人的思维、行为和态度的网络心理学领域变得越来越重要。到目前为止，网络心理学的研究只是通过自我报告的调查来收集互联网使用数据，这种方法存在许多缺点，包括人为错误、由于用户对社会合意性的担忧而产生的偏见，以及获得的数据的数量和维度的限制。PI在这个项目中的愿景是基于真实的互联网使用数据来推进人类行为评估，即在谨慎维护用户隐私预期的同时，连续、被动和不引人注意地收集互联网使用数据，而不需要人工干预。为此，PI将开发实用基础，创建两个支持互联网的应用程序(一个与在线精神健康保健有关，另一个与在线社交有关)，并利用行为心理学的结果来设计分类算法，展示基于互联网使用情况实现重大洞察和检测行为相似性(与抑郁症状和社交偏好有关)的能力。该项目建立在PI的初步工作基础上，该项目利用从Cisco NetFlow记录中收集的真实互联网使用数据来识别与抑郁症状相关的细粒度互联网使用特征，并将以大学生为主要对象进行执行。PI将在目前的项目中与来自心理和社会科学、临床精神病学和联邦调查局网络犯罪部门的专家合作。结果将包括对受误差和偏见影响最小的互联网使用情况的准确表征，以及大量用于评估人类行为的高粒度的互联网使用特征，这些共同作用将产生易于适应实际效用的见解和结论。广泛的影响：这项研究将提高我们基于互联网使用数据评估人类行为的能力。在线精神卫生保健应用程序将产生支持互联网的主动、早期和具有成本效益的精神卫生保健服务，以补充现有临床环境中的护理，而在线社交应用程序将通过利用相互的社交偏好来改善在线社交体验。这项研究在减少互联网欺诈和检测网络欺凌方面的应用是立竿见影的。国际学校将与河北大学和瑞安教育学院以及K-12学校合作，进一步加强项目外展。

Human interaction with computers, and especially with the Internet, is ever increasing. As a consequence the field of cyber-psychology, which studies the thinking, behavior and attitudes of the person using the computer, is of growing importance. To date, studies in cyber-psychology have collected Internet usage data by means of self-reported surveys only, an approach which suffers from a number of drawbacks including human error, bias due to user concerns relating to social desirability, and limits on the volume and dimensionality of the data obtained. The PI's vision in this project is to advance human behavior assessment based on real Internet usage data, that is to say Internet usage data collected continuously, passively and unobtrusively without manual intervention while carefully maintaining user privacy expectations. To these ends, the PI will develop practical foundations, create two Internet enabled applications (one relating to online mental healthcare and the other to online socializing), and leverage results in behavioral psychology to design classification algorithms that demonstrate the ability to achieve significant insights and to detect behavioral similarities (relating to symptoms of depression and preferences in social contacts) based on Internet usage. The project builds on the PI's preliminary work that exploited real Internet usage data collected from Cisco NetFlow records to identify fine-grained Internet usage features associated with symptoms of depression, and will be executed with college students as primary subjects. The PI will collaborate in the current project with experts from the psychological and social sciences, clinical psychiatry, and the FBI's cyber crimes division. Outcomes will include an accurate characterization of Internet usage minimally affected by error and bias, and a large number of Internet usage features of high granularity for assessing human behavior, which together will yield insights and conclusions readily adaptable for practical utility.Broader Impacts: This research will advance our ability to assess human behavior based on Internet usage data. The online mental healthcare application will yield Internet enabled proactive, early and cost -effective mental health care to complement care in existing clinical settings, while the online socializing application will lead to improved online social experiences by leveraging mutual social preferences. Applications of the research to mitigating Internet fraud and detecting cyber bullying are immediate. The PI will collaborate with HBCU and RUI institutions as well as K-12 schools to further enhance project outreach.