Contextual polarity and influence mining in online social networks

Computational Social Networks

Table 6 (Agreeable ideas) Modularity measures, detected communities, and significant communities at level 0.05 (based on the Wilcoxon rank-sum test)

Community detection algorithm	Modularity	Number of communities	Significant communities
With weight
Multi-level	0.54	9	6
Fast Greedy	0.53	9	8
Info Map	0.50	34	6
Edge Betweenness	0.48	12	9
Leading Eigenvector	0.48	13	9
Walk Trap	0.47	31	6
Label Propagation	0.42	30	2
Spin Glass	0.21	12	9
Without weight
Multi-level	0.54	9	6
Fast Greedy	0.53	11	9
Info Map	0.50	33	7
Edge Betweenness	0.53	9	7
Leading Eigenvector	0.51	10	7
Walk Trap	0.47	35	7
Label Propagation	0.45	35	4
Spin Glass	0.21	11	7

Each community structure is detected by one of the eight algorithms, with and without sentiment scores as weight