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Of course there a fundamental different between two methods. VOS is base on betweenness centrality and Louvain is base on modularity. This one difference of approaches of the problem generate two different views of your networks. Lovain has a resolution limits and this cause a problem with isolated nodes, but is very good to approximate to a modular structure of a network. VOS is a good to resolve a community structure in different level, but have the problem the many nodes with certain betweenness score are inside the community in the reality and not outside like frequently the method said, so in this case Louvain resolve better the structure than VOS in many case. The decision many times come from how well you know your data and the behavior of the your communities. In my case, a study metabolic network and almost all the time the communities correlated with some function in the metabolism, so the method hat I apply and select to my 'after analysis', depend on how week the algorithm describe the organization of my data and function inside the metabolism.There are a very good an extensive review of a community detection methods from Santo Fortunato: Physics Reports (2010) Vol. 46 p. 75.In this Review the VOS methods referred like 'Newman approach'. There are many, many methods for community detection and there are not a master method, all of them have a good performance to a some networks and are very bad for others. These methods that offer Pajek are too popular and using for many people, but that are not perfect.Well, I hope that you can found what method is better for you question.Best,CarlosCarlos Sanz Rodriguez
Departamento de Biología Celular
Universidad Simón Bolívar
Caracas, Apartado 89000
Telf +58-212-9064219
Laboratorio de Dinámica Estocástica
Centro de Fisica, I.V.I.C.
Caracas, Apartado 1020-A
Telf +58-212-5041919El 04/08/2013, a las 21:28, John McCreery <[log in to unmask]> escribió:Two recent runs through part of my data using the Pajek commands for, first, VOS and, second, Louvain community detection. My question is why the results using the Louvain method seem lumpier than those using the VOS method. Note, for example, that cluster 1 in the VOS distribution has 36 members, while cluster 1 using the Louvain method has 97. Using the VOS method, cluster 11 has 35 members, while cluster 11 using the Louvain method has 101. Is there a straightforward explanation why the two algorithms produce such apparently different results? Or is this just a random event?Thoughts?John (data follows)(1)==============================================================================1. VOS Clustering in N1 (637, Res=1.000000, VOS=0.9010200019, NC=54)==============================================================================Dimension: 637The lowest value: 1The highest value: 54Frequency distribution of cluster values:Cluster Freq Freq% CumFreq CumFreq% Representative----------------------------------------------------------------1 36 5.6515 36 5.6515 AD1_012 23 3.6107 59 9.2622 AD9_013 67 10.5181 126 19.7802 AD15_014 30 4.7096 156 24.4898 AD25_015 31 4.8666 187 29.3564 AD26_016 42 6.5934 229 35.9498 AD30_017 41 6.4364 270 42.3862 AD34_018 24 3.7677 294 46.1538 AD38_019 42 6.5934 336 52.7473 AD41_0110 3 0.4710 339 53.2182 AD46_0111 35 5.4945 374 58.7127 AD53_0112 19 2.9827 393 61.6954 AD61_0113 48 7.5353 441 69.2308 AD66_0114 37 5.8085 478 75.0392 AD70_0115 45 7.0644 523 82.1036 AD80_0116 7 1.0989 530 83.2025 AD84_0117 2 0.3140 532 83.5165 AD103_0118 24 3.7677 556 87.2841 AD111_0119 1 0.1570 557 87.4411 AD140_0120 13 2.0408 570 89.4819 AD143_0121 2 0.3140 572 89.7959 AD159_0122 1 0.1570 573 89.9529 AD170_0123 4 0.6279 577 90.5808 AD173_0124 1 0.1570 578 90.7378 AD181_0125 1 0.1570 579 90.8948 AD222_0126 22 3.4537 601 94.3485 AD225_0127 1 0.1570 602 94.5055 AD250_0128 3 0.4710 605 94.9765 AD289_0129 1 0.1570 606 95.1334 AD309_0130 1 0.1570 607 95.2904 AD316_0131 2 0.3140 609 95.6044 AD344_0132 2 0.3140 611 95.9184 AD346_0133 1 0.1570 612 96.0754 AD350_0134 2 0.3140 614 96.3893 AD352_0135 2 0.3140 616 96.7033 AD353_0136 1 0.1570 617 96.8603 AD354_0137 1 0.1570 618 97.0173 AD356_0138 1 0.1570 619 97.1743 AD389_0139 1 0.1570 620 97.3312 AD394_0140 2 0.3140 622 97.6452 AD395_0141 1 0.1570 623 97.8022 AD420_0142 1 0.1570 624 97.9592 AD471_0143 2 0.3140 626 98.2732 AD544_0144 1 0.1570 627 98.4301 AD546_0145 1 0.1570 628 98.5871 AD560_0146 1 0.1570 629 98.7441 AD564_0147 1 0.1570 630 98.9011 AD580_0148 1 0.1570 631 99.0581 AD592_0149 1 0.1570 632 99.2151 AD593_0150 1 0.1570 633 99.3721 AD621_0151 1 0.1570 634 99.5290 AD623_0152 1 0.1570 635 99.6860 AD624_0153 1 0.1570 636 99.8430 AD630_0154 1 0.1570 637 100.0000 AD634_01----------------------------------------------------------------Sum 637 100.0000(2)==============================================================================1. Louvain Communities in N4 (637, Res=1.000000, Q=0.601442, NC=53)==============================================================================Dimension: 637The lowest value: 1The highest value: 53Frequency distribution of cluster values:Cluster Freq Freq% CumFreq CumFreq% Representative----------------------------------------------------------------1 97 15.2276 97 15.2276 AD1_012 68 10.6750 165 25.9027 AD15_013 48 7.5353 213 33.4380 AD25_014 45 7.0644 258 40.5024 AD34_015 23 3.6107 281 44.1130 AD37_016 17 2.6688 298 46.7818 AD38_017 3 0.4710 301 47.2527 AD46_018 58 9.1052 359 56.3579 AD50_019 33 5.1805 392 61.5385 AD53_0110 11 1.7268 403 63.2653 AD61_0111 101 15.8556 504 79.1209 AD66_0112 7 1.0989 511 80.2198 AD84_0113 2 0.3140 513 80.5338 AD103_0114 14 2.1978 527 82.7316 AD110_0115 25 3.9246 552 86.6562 AD111_0116 28 4.3956 580 91.0518 AD123_0117 1 0.1570 581 91.2088 AD140_0118 2 0.3140 583 91.5228 AD159_0119 1 0.1570 584 91.6797 AD170_0120 4 0.6279 588 92.3077 AD173_0121 1 0.1570 589 92.4647 AD181_0122 1 0.1570 590 92.6217 AD222_0123 4 0.6279 594 93.2496 AD224_0124 1 0.1570 595 93.4066 AD250_0125 3 0.4710 598 93.8776 AD289_0126 1 0.1570 599 94.0345 AD309_0127 1 0.1570 600 94.1915 AD316_0128 3 0.4710 603 94.6625 AD322_0129 2 0.3140 605 94.9765 AD344_0130 1 0.1570 606 95.1334 AD350_0131 2 0.3140 608 95.4474 AD352_0132 2 0.3140 610 95.7614 AD353_0133 1 0.1570 611 95.9184 AD354_0134 1 0.1570 612 96.0754 AD356_0135 1 0.1570 613 96.2323 AD389_0136 1 0.1570 614 96.3893 AD394_0137 2 0.3140 616 96.7033 AD395_0138 1 0.1570 617 96.8603 AD420_0139 2 0.3140 619 97.1743 AD447_0140 4 0.6279 623 97.8022 AD462_0141 1 0.1570 624 97.9592 AD471_0142 2 0.3140 626 98.2732 AD544_0143 1 0.1570 627 98.4301 AD546_0144 1 0.1570 628 98.5871 AD560_0145 1 0.1570 629 98.7441 AD564_0146 1 0.1570 630 98.9011 AD580_0147 1 0.1570 631 99.0581 AD592_0148 1 0.1570 632 99.2151 AD593_0149 1 0.1570 633 99.3721 AD621_0150 1 0.1570 634 99.5290 AD623_0151 1 0.1570 635 99.6860 AD624_0152 1 0.1570 636 99.8430 AD630_0153 1 0.1570 637 100.0000 AD634_01----------------------------------------------------------------Sum 637 100.0000--
John McCreery
The Word Works, Ltd., Yokohama, JAPAN
Tel. +81-45-314-9324
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