  We extend the standard scale-free network model to include a ``triad
formation step''. We analyze the geometric properties of networks generated by
this algorithm both analytically and by numerical calculations, and find that
our model possesses the same characteristics as the standard scale-free
networks like the power-law degree distribution and the small average geodesic
length, but with the high-clustering at the same time. In our model, the
clustering coefficient is also shown to be tunable simply by changing a control
parameter - the average number of triad formation trials per time step.
