A model of opinion and propagation structure polarization in social media

Computational Social Networks

Table 3 Statistics and final m-value of the Twitter follow dataset

Hashtag	Nodes	Edges	Density	Average shortest path	Average clustering coefficient	Assortativity	Transitivity	m-value	\(\overline{q}_{\text{abs}}\)
nepal	4242	42,833	0.0048	4.038	0.265	− 0.191	0.125	2.019	0.411
germanwings	2111	7329	0.0033	4.267	0.133	− 0.127	0.111	2.031	0.278
indiasdaughter	1542	9480	0.0079	3.614	0.184	− 0.078	0.174	2.042	0.446
mothersday	2245	14,160	0.0057	4.364	0.314	− 0.016	0.364	2.057	0.445
ff	3899	63,672	0.0084	3.696	0.328	0.072	0.277	2.076	0.432
onedirection	3151	20,275	0.0041	3.226	0.103	− 0.087	0.040	2.096	0.516
jurrasicworld	4395	31,802	0.0033	3.998	0.219	− 0.143	0.142	2.215	0.408
beefban	799	6026	0.0189	3.338	0.235	− 0.063	0.215	2.244	0.422
ukraine	3382	84,035	0.0146	3.104	0.302	− 0.89	0.256	2.300	0.511
baltimore	1441	28,291	0.0272	2.861	0.227	− 0.241	0.192	2.344	0.523
indiana	946	24,328	0.544	2.530	0.351	− 0.202	0.286	2.399	0.473
ultralive	2113	16,070	0.0072	2.464	0.359	− 0.250	0.031	2.504	0.699
leadersdebate	9566	344,088	0.0075	2.547	0.310	− 0.231	0.146	2.643	0.521
nemtsov	2156	46,529	0.0200	2.692	0.322	− 0.126	0.236	2.660	0.693
russiamarch	1189	16,471	0.0233	2.798	0.285	− 0.222	0.215	2.723	0.613
sxsw	4558	91,356	0.0088	2.638	0.257	− 0.135	0.086	2.824	0.619
netanyahu	4292	297,136	0.0322	2.341	0.329	− 0.274	0.183	2.896	0.563
gunsense	1821	103,840	0.0626	2.342	0.434	− 0.159	0.312	3.288	0.720