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

From: A model of opinion and propagation structure polarization in social media

HashtagNodesEdgesDensityAverage shortest pathAverage clustering coefficientAssortativityTransitivitym-value\(\overline{q}_{\text{abs}}\)
 nepal424242,8330.00484.0380.265− 0.1910.1252.0190.411
germanwings211173290.00334.2670.133− 0.1270.1112.0310.278
indiasdaughter154294800.00793.6140.184− 0.0780.1742.0420.446
mothersday224514,1600.00574.3640.314− 0.0160.3642.0570.445
ff389963,6720.00843.6960.3280.0720.2772.0760.432
onedirection315120,2750.00413.2260.103− 0.0870.0402.0960.516
jurrasicworld439531,8020.00333.9980.219− 0.1430.1422.2150.408
beefban79960260.01893.3380.235− 0.0630.2152.2440.422
ukraine338284,0350.01463.1040.302− 0.890.2562.3000.511
baltimore144128,2910.02722.8610.227− 0.2410.1922.3440.523
indiana94624,3280.5442.5300.351− 0.2020.2862.3990.473
ultralive211316,0700.00722.4640.359− 0.2500.0312.5040.699
leadersdebate9566344,0880.00752.5470.310− 0.2310.1462.6430.521
nemtsov215646,5290.02002.6920.322− 0.1260.2362.6600.693
russiamarch118916,4710.02332.7980.285− 0.2220.2152.7230.613
sxsw455891,3560.00882.6380.257− 0.1350.0862.8240.619
netanyahu4292297,1360.03222.3410.329− 0.2740.1832.8960.563
gunsense1821103,8400.06262.3420.434− 0.1590.3123.2880.720
  1. Italic fonts indicate polarization