  Complex networks evolve and vary their structure as time goes by. In
particular, the links in those networks have both a sign and a directionality.
To understand their structural principles, we measure the network motifs, which
are patterns that appear much more than one would expect in randomized
networks, considering both link properties. We propose motif dynamics, which is
a study to investigate the change in the number of motifs, and applied the
motif dynamics to an open evolving network model and empirical data. We confirm
that a non-cyclic motif has a greater correlation with the system size than a
cyclic structural motif. Furthermore, the motif dynamics can give us insight
into the friendship between freshmen in a university.
