Thursday, January 21, 2021 - 16:00 to 18:00
SCHOOL OF COMPUTER SCIENCE
The School of Computer Science is pleased to present…
MSc Thesis Defense by: Saghi Khani
Date: Thursday January 21, 2021
Time: 4:00pm -6:00pm
Zoom Meeting URL: https://zoom.us/j/91864077769?
Passcode: If interested in attending this event, contact the Graduate Secretary at email@example.com
Social isolation can be considered as a serious health risk issue that has unignorably negative impacts on the well-being and quality of life of individuals and is harmful to healthy human development. In this research, a computational model and a couple of novel algorithms are proposed to address social isolation detection in social networks. In our model, a given community is represented by a weighted-directed social graph. An algorithm, SBSID (Structure-based Social Isolation Detection), is proposed to detect socially isolated individuals based on the graph's structure by finding the number of each individual's active friends and their influence on each other. On the other hand, each individual's demographic characteristics are represented by a set of binary attributes, and an algorithm, FBSID (Feature-based Social Isolation Detection), is presented to address social isolation based on the nodes' features in the social graph. We also propose a couple of metrics and formulas to calculate society's norms based on the social graph's structure and attributes. We have evaluated the performance of our proposed model and algorithms on a set of synthetic networks. The results show that our model is capable of finding socially isolated nodes in various sizes of graphs with high accuracy and efficiency.
Keywords: Social isolation, Social Network Analysis, Outlier Detection, Health Informatics, Computational Modeling
Internal Reader: Dr. Ziad Kobti
External Reader: Dr. Kathryn Pfaff
Advisor: Dr. Pooya Moradian Zadeh, Dr.Saeed Samet
Chair: Dr. Kalyani Selvarajah
MSc Thesis Defense Announcement
5113 Lambton Tower 401 Sunset Ave. Windsor ON, N9B 3P4 (519) 253-3000 Ext. 3716 firstname.lastname@example.org