Abstract:
Social network analysis has undergone a
renaissance with the ubiquity and quantity of content
from social media, web pages, and sensors. This
content is a rich data source for constructing and
analyzing social networks. This paper is addressing
the problems in constructing the community structure
of a networks. Graph analytics have proven to be
valuable tools in solving this challenges. Network
become an intensive subject of research for example
in computer science, networking, network sciences
etc., a growing need for valid and useful dataset is
presented. Useful ways of addressing this problem
are sampling based on the nodes (user)ids in the
social network until sufficient amount of data has
been obtained. This paper is presented the
community detection algorithm such as modularity
methods. Then compare the given dataset Vs
different data set.
