  Nature-inspired optimization Algorithms (NIOAs) are nowadays a popular choice
for community detection in social networks. Community detection problem in
social network is treated as optimization problem, where the objective is to
either maximize the connection within the community or minimize connections
between the communities. To apply NIOAs, either of the two, or both objectives
are explored. Since NIOAs mostly exploit randomness in their strategies, it is
necessary to analyze their performance for specific applications. In this
paper, NIOAs are analyzed on the community detection problem. A direct
comparison approach is followed to perform pairwise comparison of NIOAs. The
performance is measured in terms of five scores designed based on prasatul
matrix and also with average isolability. Three widely used real-world social
networks and four NIOAs are considered for analyzing the quality of communities
generated by NIOAs.
