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.
