Table 3. LC performance on different artificial datasets conditions.

Average degree	4				8				12
pinside	EQ	PD	IGP	CN	EQ	PD	IGP	CN	EQ	PD	IGP	CN
0.9	0.118	0.319 *	0.056	17.1	0.295 *	0.839 *	0.224	7.4	0.289 *	0.616 *	0.146	7.9
0.8	0.111	0.436 *	0.096	16.8	0.148	0.452 *	0.071	21.6	0.177 *	0.586 *	0.098	17.3
0.7	0.086	0.327 *	0.046	14.0	0.088	0.152 *	0.109	27.1	0.090 *	0.557 *	0.118	28.8
0.6	0.086	0.295 *	0.069	16.1	0.078	0.260 *	0.095	31.4	0.016	0.108	0.725 *	14.4
0.5	0.087	0.284 *	0.061	15.5	0.064	0.208 *	0.095	33.7	0.004	0.114	0.901 *	1.0

^*the bold data marked with an asterisk (*) is the best value with the same location in Tables 2–4.

^**EQ: Extended Quality of modularity; IGP: In-Group-Proportion; PD: Partition Density; CN: Communities Number.

To avoid accidental influence of single artificial network, all types of evaluation values are average values of 10 networks in each condition.