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Proceedings ArticleDOI

Analysis of Peer Group Behavior Among University Students

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TLDR
The preliminary results from this investigation reveal that students social interactions are not limited to one but several groups, and the satisfaction levels associated with each type of group are indicative of the average time spent engaging with said group(s).
Abstract
Satisfactory peer group interactions within a university, through the formation of close associations, define a student's personality and help in deterring the rise of depression caused by academic, financial or emotional troubles. In this work, we conduct a pre-study survey of 177 students in a University setting to assess the requirement for a smartphone-based study to detect and monitor group formation, evolution and engagement. The preliminary results from this investigation reveal that students social interactions are not limited to one but several groups, and the satisfaction levels associated with each type of group are indicative of the average time spent engaging with said group(s). Intra-group bond strength took precedence as a satisfaction determinant over the location or activity engaged in. Further, we present design recommendations for a minimally invasive smartphone-based study.

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Proceedings ArticleDOI

Anomaly detection in crowds using multi sensory information

TL;DR: The approach is the first to detect any unusual behaviour in crowd with non-visual data, which is simple to train and easy to deploy and presented for public research as there is no such dataset available to perform experiments on crowds for detecting unusual behaviours.
Proceedings ArticleDOI

Application for the UbiComp 2018 Broadening Participation Workshop

TL;DR: I, Sahiti Kunchay, is a student of the College of Information Sciences and Technology at The Pennsylvania State University, enrolled in the IST's PhD program's Fall 2018 cohort, with the expected date of graduation being May 2023.
References
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Proceedings ArticleDOI

StudentLife: assessing mental health, academic performance and behavioral trends of college students using smartphones

TL;DR: A Dartmouth term lifecycle is identified in the data that shows students start the term with high positive affect and conversation levels, low stress, and healthy sleep and daily activity patterns, while stress appreciably rises while positive affect, sleep, conversation and activity drops off.
Proceedings ArticleDOI

Discovering Shifts to Suicidal Ideation from Mental Health Content in Social Media

TL;DR: This paper develops a statistical methodology to infer which individuals could undergo transitions from mental health discourse to suicidal ideation, and utilizes semi-anonymous support communities on Reddit as unobtrusive data sources to infer the likelihood of these shifts.
Journal ArticleDOI

Next-generation psychiatric assessment: Using smartphone sensors to monitor behavior and mental health.

TL;DR: Smartphones can be harnessed as instruments for unobtrusive monitoring of several behavioral indicators of mental health and creative leveraging of smartphone sensing could provide novel opportunities for close-to-invisible psychiatric assessment at a scale and efficiency that far exceeds what is currently feasible with existing assessment technologies.
Proceedings ArticleDOI

Passive and In-Situ assessment of mental and physical well-being using mobile sensors

TL;DR: The feasibility of a multi-modal mobile sensing system to simultaneously assess mental and physical health is shown and different metrics that reflect the results of commonly used surveys for assessing well-being by the medical community are derived.
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