Detection of Communities over the social network, also known as network clustering, has been widely studied in the past few years. The objective of community detection is to identify strongly connected components in a complex network. It reveals how people connect and interact with each other. In the real world, however, a person is engaged in several traits of connections, these connections or social ties carry other different challenges in community detection. More than one trait of connections can be exhibited as a multiplex network that contained itself a collection of multiple interdependent networks, where each network represents a trait of the connections. In this literature, we provide readers with a brief understanding of multilayer networks, community detection methods, and proposed an approach to detect community and its structure using a multilayer modularity method on the Facebook page. The study also investigates how strong the ties between users and their polarity towards the page over the span of time. The results successfully remove the isolates from the network and built a well-defined structure of the community.
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