Date of Award

2017

Degree Type

Thesis

Degree Name

M.Sc.

Department

Computer Science

First Advisor

Kobti, Ziad

Keywords

Community Detection, Dynamic Social Networks, Knowledge Sharing, Multi-Population Cultural Algorithm, Prior Knowledge

Rights

CC BY-NC ND 4.0

Abstract

The relationship between a community and the knowledge that it encompasses is a fundamentally important aspect of any social network. Communities, with some level of similarity, implicitly tend to have some level of similarity in their knowledge as well. This work does the analysis on the role of prior knowledge in Multi-Population Cultural Algorithm (MPCA) for community detection in dynamic social networks. MPCA can be used to find the communities in a social network. The knowledge gained in this process is useful to analyze the communities in other social networks having some level of similarity. Our work assumes that knowledge is an integral part of any community of a social network and plays a very important role in its evolution. Different types of networks with levels of non-similarity are analyzed to see the role of prior knowledge while finding communities in them.

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