merged

Using Social Network Analysis to Elucidate UMT Students Network
Lingeswaran A/L Ramachandran
Supervisor: Assoc. Prof. Dr. Gobithaasan Rudrusamy
Bachelor of Science (Computational Mathematics)
School of Informatics and Applied Mathematics
Social network analysis is used to study the structure of the graph or pattern that contains
two basic components of individual vertex (students) and edges (connections between
students). The aim of this study is to identify individual, intermediate, group measures
and reciprocity between UMT students. The objectives are to identifying class
representative, to identify subgroups which can be used to divide the students into
groups for completing assignments and to find the reciprocity between students. The
collected data is represented in the form of adjacency matrix from UMT 3rd year
computational mathematics students for subject geometric modelling by survey form and
UCINET 6/ Netdraw are employed to measure for centrality, Girvan Newman and
cohesion. We identify class representative using in-degree, betweeness whereas outdegree,
in-closeness and out-closeness not suitable. We identify subgroups by doing
clustering using Girvan Newman to identify academic standard of students in groups. We
identify reciprocity by visualise student network.
942 | UMT UNDERGRADUATE RESEARCH DAY 2018