EUSN - bavla/biblio GitHub Wiki
EUSN 2023
Normalizacija
- preberem omrezje WAr
- info, pogledam stevilo vrstic
- pozenem macro norma2.mcr - vnesem stevilo vrstic
Kako dobim Cn
- transponiram normalizirano omrežje - Netwrok/Two Mode/Transpose Two mode
- izbrem transponirano in normalizirano omrežje
- pomnožim omrežji - Networks/Multiply Networks
Sodelovalnost(a) = 1- weighted degree(a)/degree(a)
- izberem normalizirano omrežje WAr
- Network/Two mode network/Partition into 2 modes, da dobimo avtorje in dela
- Degree (a) - Network/Vector/Degree/Input
- Izrežem avtorje - Izberemo degree in partition Operations/Vector + Partition
- weighted degree (a) - Network/Vector/Weighted Degree/Input
- Izrežem avtorje - Izberemo weighted degree in partition Operations/Vector + Partition
- izberem oba vektorja in ju delim - Vectors/Divide
- vektor pomnožim z -1 - Vecgtor/Transform/Multiply by -1
- dodam +1 in dobim vrednost sodelovalnosti - Vector/Transform/Add constant/1
- izberem omrežje sodelovanja, zato da so vidna imena avtorjev
Izdelava tabele
- izberem Degree vector, po katerem hocem urejati - Vector/Make Permutation - to naredim samo za degree, po katerem bodo vsi urejeni!
- za obratni vrstni red (padajoči) izberem - Permutation/Mirror Permutation (naredi padajoče)
- izberem spet Degree in permutacijo - Operations/Vector + Permutation/Reorder Vector
- Še 2x ponovim za Weighted dgeree in soeldoivalnost
- wdeg naredim samo da skopiram, ker gre za permautacijo na tem vektorju, za deg naredim izvoz prvih 60 vrednosti iz TextPada
Avtorji glede na sodelovanje produktivnost
Rank Sodelovalnost Weighted degree Degree Id
--------------------------------------------------------
1 0.580693670 38.995488722 93.0000 KRIEGER_J
2 0.487718009 41.494841270 81.0000 DUCKWORT_A
3 0.621779732 29.879401154 79.0000 [ANONYMO
4 0.751688968 16.388528139 66.0000 BERG-SOR_I
5 0.754371760 13.263924964 54.0000 BERLIN_O
6 0.129078014 40.933333333 47.0000 BERNETT_H
7 0.588957902 18.907936508 46.0000 BOLLING_H
8 0.709856684 12.766305916 44.0000 BRICHFOR_M
9 0.737734488 11.277417027 43.0000 CHAPPELE_E
10 0.738431638 10.462734488 40.0000 EGGERS_E
11 0.109544695 33.837301587 38.0000 GROSSET_Y
12 0.310060060 25.527777778 37.0000 GUTTMANN_A
13 0.774406458 8.121367521 36.0000 HEIMERZH_P
14 0.446405523 19.929401154 36.0000 HARDMAN_K
15 0.481204906 17.120238095 33.0000 HERZOG_M
16 0.730097512 8.906782107 33.0000 INTERNAT_H
17 0.528250244 14.624242424 31.0000 KREBS_H
18 0.287596006 22.084523810 31.0000 KEYS_B
19 0.763126566 7.106203008 30.0000 KRUGER_M
20 0.310344828 20 29.0000 KRUGER_A
21 0.429761905 15.966666667 28.0000 LIPPE_G
22 0.607187555 10.998748474 28.0000 LARGE_D
23 0.082304527 24.777777778 27.0000 OWEN_D
24 0.538227513 12.467857143 27.0000 NIELSEN_N
25 0.057407407 25.450000000 27.0000 MILLERMA_G
26 0.379894180 16.742857143 27.0000 MANDELL_R
27 0.168062904 22.462301587 27.0000 LUCAS_J
28 0 26 26.0000 RAIOLA_G
29 0.620787546 9.859523810 26.0000 PHILLIPS_B
30 0.059829060 24.444444444 26.0000 PFISTER_G
31 0.644666667 8.883333333 25.0000 YTTERGRE_L
32 0.266474747 18.338131313 25.0000 KOC_H
33 0.746972703 6.072655123 24.0000 AYGUL_A
34 0.515873016 11.619047619 24.0000 AYDOS_L
35 0.348214286 15.642857143 24.0000 AYCAN_K
36 0.251074735 17.974206349 24.0000 ARINC_K
37 0.757423942 5.821825397 24.0000 ACIKEL_C
38 0.398067633 13.844444444 23.0000 BRIAN_S
39 0.094202899 20.833333333 23.0000 BILGE_M
40 0.326708075 15.485714286 23.0000 BENCTEUX_P
41 0.423188406 13.266666667 23.0000 BALDI_S
42 0.393127706 13.351190476 22.0000 CARROLL_C
43 0.031746032 20.333333333 21.0000 SANAL_H
44 0.038095238 20.200000000 21.0000 PERCIN_S
45 0.524489796 9.985714286 21.0000 OZGONUL_E
46 0.035714286 20.250000000 21.0000 OOMMEN_A
47 0.153174603 17.783333333 21.0000 MC_A
48 0.546107332 9.531746032 21.0000 FOX_E
49 0.072562358 19.476190476 21.0000 CINAR_C
50 0.384523810 12.309523810 20.0000 KUNST-_G
51 0.467696609 10.646067821 20.0000 HANTAU_C
52 0.306666667 13.866666667 20.0000 NARCIS_N
53 0.270833333 14.583333333 20.0000 CRISTINA_H
54 0.424868421 11.502631579 20.0000 CRISTINA_N
55 0.512896825 9.742063492 20.0000 CEZAR_H
56 0.465416667 10.691666667 20.0000 VANDEN_T
57 0.040000000 19.200000000 20.0000 UZ_A
58 0.323690476 13.526190476 20.0000 SONMEZ_G
59 0.545654762 9.086904762 20.0000 SEVIM_Y
60 0.090000000 18.200000000 20.0000 SCHUURMA_A
Razporejeni glede na dejanski prispevek
Rank Vertex Value Id
--------------------------------------------------------
1 2 41.4948 DUCKWORT_A
2 6 40.9333 BERNETT_H
3 1 38.9955 KRIEGER_J
4 11 33.8373 GROSSET_Y
5 3 29.8794 [ANONYMO
6 28 26.0000 PFISTER_G
7 12 25.5278 GUTTMANN_A
8 25 25.4500 MILLERMA_G
9 23 24.7778 LUCAS_J
10 30 24.4444 RAIOLA_G
11 27 22.4623 OWEN_D
12 18 22.0845 KREBS_H
13 39 20.8333 BENCTEUX_P
14 43 20.3333 CINAR_C
15 46 20.2500 OOMMEN_A
16 44 20.2000 FOX_E
17 20 20.0000 KRUGER_A
18 14 19.9294 HEIMERZH_P
19 49 19.4762 SANAL_H
20 57 19.2000 CRISTINA_H
21 7 18.9079 BOLLING_H
22 32 18.3381 KOC_H
23 60 18.2000 KUNST-_G
24 64 18.1250 ESTRIGA_M
25 36 17.9742 AYDOS_L
26 47 17.7833 OZGONUL_E
27 15 17.1202 HERZOG_M
28 86 17.0000 BIENER_K
29 84 17.0000 PHILIPSE_H
30 26 16.7429 NIELSEN_N
31 73 16.5000 GARGANTA_J
32 4 16.3885 BERG-SOR_I
33 88 16.2500 JACKSON_D
34 21 15.9667 LARGE_D
35 35 15.6429 AYCAN_K
36 40 15.4857 BILGE_M
37 92 15.2000 KOPLAN_J
38 100 15.1250 MALIA_J
39 111 15.0000 CASTRO_F
40 70 14.8333 FEU
41 17 14.6242 KEYS_B
42 53 14.5833 UZ_A
43 90 14.3333 JORGENSE_U
44 123 14.0000 KJONNIKS_L
45 118 14.0000 GONZALEZ_M
46 117 14.0000 GARCIA-A_A
47 52 13.8667 SONMEZ_G
48 38 13.8444 BALDI_S
49 74 13.7833 GRECO_P
50 67 13.7500 AQUINO_R
51 58 13.5262 NARCIS_N
52 71 13.5000 FLICK_U
53 42 13.3512 CARROLL_C
54 41 13.2667 BRIAN_S
55 5 13.2639 BERLIN_O
56 158 13.0000 MURACHOV_J
57 83 12.8338 VANGALEN_W
58 8 12.7663 BRICHFOR_M
59 62 12.7500 TROFIN_E
60 125 12.7500 LARA_D
61 85 12.6861 ANDRENSA_A
62 24 12.4679 MANDELL_R
63 94 12.4500 MAEHLUM_S
64 79 12.4000 PURDY_L
65 87 12.3333 CHAN_K
66 50 12.3095 SCHUURMA_A
67 127 12.2361 LOHSE_K
68 98 12.0333 WOLF_G
69 182 12.0000 CARR_A
70 176 12.0000 BAILEY_S
71 175 12.0000 ASHWORTH_A
72 163 12.0000 REINOLD_M
73 106 11.6583 BEBETSOS_G
74 34 11.6190 ARINC_K
75 114 11.5333 DEVIS_J
76 54 11.5026 VANDEN_T
77 183 11.5000 COOPER_R
78 78 11.3861 MESQUITA_I
79 9 11.2774 CHAPPELE_E
80 69 11.1917 BUNKER_D
PS sredice
- izberem omrežje sodelovanja
- Network/Create Vector/Generalized Core/Sum/All
- Pogledamo info vectorja in vidimo glede na kateri threshold vzamemo avtorje - Vector/Make partition/By intervals/Selected threeshold/stevilo
- Izberemo izlocene enote - Operations/Netwrok + Partition/Extract/Subnetwork
- Dobili smo sredično razbitje
- Uporabim začeten weighted degree vector in partition od vektorja - Operations/Vector + partition/Extract subvector/2
- Izločim zanke
- narišem omrežje - Draw/Network + First partition + First vector
Stroga normalizacija
- osnovno omrežje -> norm2p
- izberem Transponiranega normaliziranega in storgo normaliziranega
- zmnožim omrežji
- zbrišem zanke
Stroge sredice vrednosti
Rank Vertex Value Id
--------------------------------------------------------
1 54 10.0000 VANDEN_T
2 1570 10.0000 ETTEMA_G
3 1723 9.5016 FORD_K
4 1624 9.5016 HEWETT_T
5 1094 9.5016 MYER_G
6 1693 5.6667 POBAR_M
7 1692 5.6667 IVASIC-K_M
8 502 4.8823 CHELLY_M
9 975 4.8823 SCHWESIG_R
10 3842 4.8823 SHEPHARD_R
11 854 4.8823 HERMASSI_S
12 357 4.6667 DEBANNE_T
13 1294 4.6667 LAFFAYE_G
14 1954 4.5864 KROSSHAU_T
15 1114 4.5864 BAHR_R
16 429 4.5096 MYKLEBUS_G
17 6375 4.0000 RAMIREZ-_G
18 6374 4.0000 FLORES-R_J
19 921 3.9333 LOFFING_F
20 5297 3.9333 HAGEMANN_N
21 919 3.8238 KRISTIAN_E
22 496 3.7476 BAKER_J
23 2829 3.7476 SCHORER_J
24 388 3.6870 ENGEBRET_L
25 1715 3.6667 AAGAARD_P
26 206 3.6667 MICHALSI_L
27 6571 3.6667 MADSEN_K
28 1386 3.6000 STEFFEN_K
29 564 3.6000 OLSEN_O
30 2189 3.2667 MOK_K
31 1507 3.2437 NILSTAD_A
32 1451 3.1667 RULENCE-_P
33 1432 3.1667 FRUCHART_E
34 19068 3.1333 BRENT_J
35 3764 3.0000 GUMUS_H
36 3319 3.0000 GENCOGLU_C
37 5496 3.0000 WADE_M
38 2281 3.0000 ALSHARJI_K
39 973 3.0000 PONTAGA_I
40 5376 3.0000 TILP_M
41 4490 3.0000 SCHRAPF_N
42 1099 3.0000 ZIDENS_J
43 1690 3.0000 WEGNER_M
44 286 3.0000 WEBER_J
45 3982 2.9333 FREESTON_J
46 20209 2.9333 ROONEY_K
47 3171 2.7643 ALOUI_G
48 5337 2.7643 GAAMOURI_N
49 2538 2.7643 HAMMAMI_M
50 8441 2.7643 HAYES_L
51 484 2.7244 BENCKE_J
52 442 2.7244 ZEBIS_M
53 3418 2.7067 YU_B
54 9174 2.7067 GARRETT_W
55 367 2.6667 HASTIE_P
56 78 2.6667 MESQUITA_I
57 4706 2.6667 FARIAS_C
58 814 2.6667 BJORNDAL_C
59 513 2.6667 RONGLAN_L
60 9826 2.6667 FONTAYNE_P
61 2681 2.6667 MACMAHON_C
62 2680 2.6667 BALL_K
63 2679 2.6667 PARRINGT_L
64 253 2.6619 WAGNER_H
65 1677 2.6619 VONDUVIL_S
66 2487 2.6619 MULLER_E
67 2046 2.6333 FUCHS_P
68 243 2.6333 LUTEBERG_L
69 2068 2.6333 SPENCER_M
70 432 2.6048 CLARSEN_B
71 476 2.6000 KATIC_R
72 474 2.6000 SRHOJ_V
73 910 2.6000 CAVALA_M
74 1540 2.6000 MILANOVI_D
75 380 2.6000 ROGULJ_N
76 1195 2.6000 VULETA_D
77 1903 2.5619 CAMACHO-_A
78 2065 2.5619 BRAZO-SA_J
79 2064 2.5619 CAMACHO-_M
80 1095 2.5333 PETUSHEK_E
Avtorji, ki so skupaj napisali največ del
-
izberem WAr in transporniran WAr (Network/2-mode network/Transpose 2-mode)
-
zmnožim omrežji Netwroks/Multiply networks
-
pogledam info omrežja, da vidim od katere vrednosti naprej je malo sooavtorstev, ki jih bi lažje prikazal
-
izvržem zanke
-
npr. 10x soavtorstev, izvlečem vrednosti višje od 10 - Network/Create new network/Transform/Remove/Lines with values/Lower than/10
-
Partition/Degree/All
-
Izvržem tiste, ki imajo degree 0, Operations/Netwrok + Partition/Extract/1./1-*
-
Network/Create New network/Components/Weak
-
Spremenim usmerjene v neusmerjene povezave -> narišem omrežje, označim povezave s števili
-
izločim določeno omrežje
-
na info partiiona pogledam katetero je razbitje, ki ga želim izločit
-
Operations/Extract/Številka razbitja
Otoki
-
izberem omrežje strogih soavtorstem, dam v neusmerjene povezave
-
vklopimo stikalo - Netwrok/Create Partition/Islands/Generate network with islands
-
Generiram otoke - Netwrok/Create Partition/Islands/Line weights (izbral sem 5 in 30)
-
Uredim otoke po velikosti - Partition/Canopnical Partition/With decreased frequencies
-
Izločim samostojna vozliščac - Operations/Network + partitions/Extract
-
indetificiram določenega avtorja - Network/Info/Vertex Label -> Vertex Number, s tem dobim na katerem mestu je določen avtor
-
pogledam kateremu otoku pripada avtor - lupa in pogledam stevilko
Postopek Keywords
Normalizacija
- preberem omrezje WKr
- info, pogledam stevilo vrstic
- pozenem macro norma2.mcr - vnesem stevilo vrstic
Kako dobim Cn
- transponiram normalizirano omrežje - Netwrok/Two Mode/Transpose Two mode
- izbrem transponirano in normalizirano omrežje
- pomnožim omrežji - Networks/Multiply Networks
- Pri ustvarjanju omrežij moram odstraniti loope in simetrizirat (z vsoto) - ostalo enako kot pri prejsnjem omrezju
Kaywords - Prerez 100
- lower than
- degree
- extract
Keywords - otoki
- Naredim otoke kot prej
- Pogledam kje je handball in ga odstranim, da vidim povezave z ostalimi točkami
Keywords - sredice
- Vector/Generalized core/Sum/All
Keywords pojavljanje v člankih
-
Narejeni postopki: https://github.com/bavla/SocNet/wiki/CoauthKeys
-
Članek: Towards a systematic description of the field using keywords analysis: main topics in social networks
-
izbira omrežja WKr
-
razbitje na obe množici W in K - Network/Two-mode network/Partition
-
normaliziram omrežje - info/št. vrstic, macro/play/norm2
-
transfoniram normalizirano omrežje
-
izberem transponirano in normalitzirano omrežje in ju pomnozim - Networks/Multiply Networks
-
To je zdaj omrežje nKK
-
izberemo normalizirno omrežje in izračunam vektor vhodnih stopenj - Vector/Degree/input
-
ven poberem Keywords del - Operations/Vector + Partition/Extract/2
-
isto naredimo z weighted degree, razlika weighted degree
-
Naredimo permutacijo za Wdeg - izberem Wdeg - Vector/Make permutation -> Permutation/Mirror Permutation -> shraqnim vektor degree.vec
-
Izberem Vektor extracted degree (navaden) - Operations/Vector + Permutation/Reorder
-
Nredim info +60 za wdeg extracted in skopiram v text pad
-
uvozim degree.vec in prvih 60 vrednosti skopiram zraven wdeg
Rank Vertex Weighted degree| Degree
--------------------------------------------------------
1 handball 53.3204 2888
2 player 27.7675 2033
3 study 24.8481 2213
4 team 22.8018 1651
5 sport 21.3032 1803
6 result 19.2120 1799
7 performance 16.3606 1392
8 use 15.8454 1490
9 injury 13.9686 1031
10 athlete 13.2078 1208
11 female 12.7995 994
12 training 12.7945 1089
13 analysis 12.7104 1142
14 difference 11.8686 1114
15 effect 11.2906 914
16 test 11.0310 1062
17 0 11.0190 1197
18 aim 10.8468 1014
19 method 10.4889 1026
20 elite 10.4638 868
21 1 9.9580 1072
22 significant 9.9273 974
23 2 9.8773 1036
24 male 9.5901 881
25 year 9.5155 940
26 level 9.3332 867
27 group 9.2978 916
28 p 9.2891 984
29 conclusion 9.1859 993
30 different 9.1122 797
31 age 8.8219 891
32 physical 8.7570 824
33 time 8.7093 806
34 compare 8.4776 848
35 measure 8.4689 817
36 3 8.4367 900
37 perform 8.2012 805
38 soccer 8.0059 750
39 increase 7.7239 782
40 game 7.5818 576
41 basketball 7.4941 660
42 strength 7.4579 673
43 high 7.4281 747
44 risk 7.3647 722
45 knee 7.2260 660
46 ligament 7.2181 630
47 control 7.1534 697
48 < 7.1079 772
49 purpose 7.1067 680
50 play 7.0790 606
51 analyse 7.0070 627
52 lower 6.9895 699
53 datum 6.9334 663
54 cruciate 6.7918 597
55 factor 6.7799 625
56 base 6.6291 614
57 throw 6.5802 477
58 jump 6.5124 615
59 5 6.4979 713
60 exercise 6.3127 603
Otoki keywords 3-50
Otoki keywords brez top 3
Ustvarjanje omrežja AK - WAr(t) x WKr
- Preberem WAr in ga normaliziriam -> transponiram
- kot drugo izberem normalizirano WKr in ju pomnožim -> nAK
- izberem razbitje na otoke
- izberem otok, ki ga želim pogledat
- Partition/Binarize Pertition/Številka otoka
- To je zdaj samo rabitje mnozice A
- Izberem omrežje nAK -> Določim velikost K-ja na Info/Netwrok/Columns -> kopiram
- Partition/Create Constant Partition/Številka columns od prej in 1 - to naredim samo 1x
- Izdelava razbitja SLO -> Kot prvo partition binarized izbranega otoka, kot drugo Constant partition -> Parititons/Fuse partitions
- Ustvarimo podomrežje -> izberem omrežje nAK in razibtje SLO -> Operations/Network + Partition/Extract/1-* -> dobimo podomrežje ki pripada avotrjem iz otoka
- Na tem omrežju izračunam weighted indegree - Network/Vector/Weighted degree/indegree
- Iz tega podomrežja naredimo razbitje 2-mode na A in K -> Network/2-mode/Partition into 2-modes
- Operations/Vector + Parititon/Extract/2
- Izberem omrežje nKK (zato, da so vidna imena) -> info vektorja
Omrežje Šibila - 57
- Glavni avtor: Dinko Vuleta - https://www.kif.unizg.hr/djelatnici/dinko.vuleta
- Področje raziskovanja: Kineziologija v povezavi z rokometom
Rank Vertex Value Id
--------------------------------------------------------
1 9 0.3594 handball
2 331 0.2505 play
3 153 0.2420 difference
4 351 0.2160 position
5 164 0.1872 analysis
6 59 0.1848 player
7 169 0.1844 team
8 345 0.1780 significant
9 61 0.1594 result
10 287 0.1573 use
11 308 0.1396 test
12 299 0.1380 performance
13 826 0.1362 statistically
14 80 0.1354 study
15 346 0.1316 variable
16 316 0.1288 physical
17 447 0.1247 activity
18 31 0.1199 body
19 528 0.1166 time
20 268 0.1102 p
21 109 0.1101 aim
22 391 0.1077 male
23 1174 0.1052 composition
24 62 0.1051 determine
25 469 0.1048 research
26 69 0.1032 +
27 230 0.1029 female
28 1014 0.0986 relate
29 386 0.0980 sample
30 318 0.0967 rate
31 363 0.0963 fitness
32 317 0.0952 level
33 124 0.0942 group
34 312 0.0929 elite
35 187 0.0907 different
36 488 0.0903 characteristic
37 812 0.0889 obtain
38 332 0.0858 competition
39 244 0.0852 movement
40 602 0.0848 3
41 233 0.0839 0
42 1504 0.0816 technical
43 580 0.0811 2
44 504 0.0801 shot
45 434 0.0785 assess
46 559 0.0781 01
47 8 0.0771 year
48 108 0.0770 age
49 652 0.0766 average
50 342 0.0765 match
Omrežje 1
- Glavni avtor: Timothy E. Hewett - https://www.researchgate.net/profile/Timothy-Hewett
- Področje raziskovanja: Športna medicina
- Glavna soavtorja: Gregory D. Myer (https://scholar.google.com/citations?user=dxI8iXEAAAAJ&hl=en), Kevin R. Ford (https://scholar.google.com/citations?user=xL2RzG0AAAAJ&hl=en)
Rank Vertex Value Id
--------------------------------------------------------
1 179 0.7972 injury
2 575 0.7032 knee
3 230 0.6789 female
4 773 0.6685 ligament
5 755 0.6628 cruciate
6 594 0.6429 risk
7 1166 0.6128 acl
8 767 0.5981 anterior
9 169 0.5776 team
10 9 0.5731 handball
11 265 0.5687 athlete
12 591 0.5457 prevention
13 555 0.5121 neuromuscular
14 221 0.4751 control
15 59 0.4323 player
16 278 0.4173 high
17 106 0.4117 training
18 164 0.3820 analysis
19 286 0.3728 increase
20 80 0.3568 study
21 340 0.3381 soccer
22 953 0.3295 basketball
23 153 0.3169 difference
24 659 0.3151 factor
25 4227 0.2971 landing
26 794 0.2960 biomechanic
27 287 0.2886 use
28 61 0.2859 result
29 11 0.2841 sport
30 572 0.2788 effect
31 578 0.2607 abduction
32 455 0.2585 program
33 220 0.2539 conclusion
34 1086 0.2537 demonstrate
35 692 0.2537 force
36 517 0.2425 mechanism
37 102 0.2416 purpose
38 186 0.2403 design
39 71 0.2370 1
40 532 0.2365 joint
41 1406 0.2324 reduce
42 268 0.2295 p
43 1138 0.2249 greater
44 580 0.2234 2
45 1409 0.2219 intervention
46 251 0.2218 lower
47 602 0.2170 3
48 87 0.2163 decrease
49 58 0.2162 measure
50 147 0.2131 school
J Gonzalez
- Glavni avtor: Gonzalez-Badillo JJ - https://scholar.google.es/citations?user=xmX0Wq4AAAAJ&hl=es
- Področje raziskovanja: Strength Training, Sport science
Rank Vertex Value Id
--------------------------------------------------------
1 9 0.7896 handball
2 59 0.7352 player
3 80 0.5662 study
4 169 0.5290 team
5 299 0.4835 performance
6 61 0.4477 result
7 84 0.4134 velocity
8 374 0.3670 throw
9 11 0.3547 sport
10 106 0.3293 training
11 580 0.3216 2
12 109 0.3185 aim
13 849 0.3095 maximal
14 153 0.3082 difference
15 187 0.3073 different
16 512 0.2783 experience
17 108 0.2732 age
18 345 0.2630 significant
19 164 0.2586 analysis
20 1768 0.2538 m
21 426 0.2495 ball
22 31 0.2449 body
23 969 0.2425 overarm
24 692 0.2413 force
25 553 0.2409 strength
26 391 0.2380 male
27 572 0.2345 effect
28 287 0.2320 use
29 102 0.2257 purpose
30 233 0.2225 0
31 18 0.2216 goal
32 695 0.2108 kinematic
33 305 0.2013 analyse
34 1077 0.1991 season
35 71 0.1971 1
36 8 0.1938 year
37 312 0.1913 elite
38 222 0.1807 compare
39 308 0.1754 test
40 234 0.1753 perform
41 440 0.1736 accuracy
42 388 0.1704 16
43 1014 0.1698 relate
44 251 0.1686 lower
45 244 0.1619 movement
46 316 0.1617 physical
47 2564 0.1612 resistance
48 175 0.1611 comparison
49 62 0.1602 determine
50 268 0.1563 p
51 711 0.1551 height
52 230 0.1543 female
53 398 0.1541 9
54 669 0.1534 coordination
55 614 0.1518 questionnaire
56 304 0.1517 professional
57 585 0.1507 examine
58 436 0.1500 20
59 69 0.1474 +
60 151 0.1470 base
--------------------------------------------------------
All islands 5-30
Menyhart
Rank Vertex Value Id
--------------------------------------------------------
1 31 0.0079 body
2 126 0.0079 lead
3 251 0.0079 lower
4 2004 0.0079 recommend
5 1997 0.0079 draw
6 61 0.0079 result
7 489 0.0079 n
8 121 0.0079 identify
9 1946 0.0079 contraction
10 1936 0.0079 screening
11 1922 0.0079 combine
12 3805 0.0079 lifestyle
13 944 0.0079 100
14 58 0.0079 measure
15 233 0.0079 0
16 3731 0.0079 ecg
17 1856 0.0079 recommendation
18 921 0.0079 stress
19 1823 0.0079 family
20 907 0.0079 referee
21 1798 0.0079 significance
22 896 0.0079 psychological
23 55 0.0079 history
24 6992 0.0079 plaque
25 6991 0.0079 cct
26 6990 0.0079 myocardial
27 6989 0.0079 coronary
28 6988 0.0079 9years
29 6987 0.0079 bridge
30 6986 0.0079 cardiology
31 6985 0.0079 antihypertensive
32 6984 0.0079 holter
33 6983 0.0079 dyslipidaemia
34 6982 0.0079 cmr
35 6981 0.0079 precompetition
36 6980 0.0079 monitorization
37 108 0.0079 age
38 3482 0.0079 38%
39 3477 0.0079 echocardiography
40 867 0.0079 blood
41 866 0.0079 undergo
42 107 0.0079 hour
43 1713 0.0079 percentage
44 106 0.0079 training
45 842 0.0079 rest
46 104 0.0079 change
47 209 0.0079 10
48 6628 0.0079 58%
49 820 0.0079 week
50 811 0.0079 importance
51 3239 0.0079 therapy
52 201 0.0079 modify
53 1603 0.0079 number
54 787 0.0079 tomography
55 391 0.0079 male
56 6229 0.0079 elevate
57 1556 0.0079 examination
58 3100 0.0079 22%
59 11 0.0079 sport
60 3069 0.0079 16%
--------------------------------------------------------
Island 2
Rank Vertex Value Id
--------------------------------------------------------
1 9 1.2197 handball
2 179 1.1737 injury
3 169 0.8883 team
4 59 0.7427 player
5 80 0.6459 study
6 11 0.5922 sport
7 230 0.5858 female
8 575 0.5624 knee
9 773 0.5204 ligament
10 755 0.4906 cruciate
11 594 0.4883 risk
12 1166 0.4815 acl
13 591 0.4579 prevention
14 265 0.4449 athlete
15 312 0.4222 elite
16 243 0.4128 method
17 61 0.4086 result
18 287 0.3942 use
19 164 0.3911 analysis
20 71 0.3762 1
21 233 0.3674 0
22 221 0.3663 control
23 517 0.3632 mechanism
24 220 0.3601 conclusion
25 602 0.3551 3
26 532 0.3548 joint
27 1441 0.3414 prospective
28 1157 0.3355 football
29 214 0.3203 youth
30 8 0.3146 year
31 767 0.3135 anterior
32 340 0.3116 soccer
33 342 0.3054 match
34 187 0.3007 different
35 580 0.2952 2
36 695 0.2889 kinematic
37 267 0.2865 motion
38 358 0.2855 4
39 1139 0.2798 incidence
40 151 0.2729 base
41 523 0.2640 6
42 308 0.2618 test
43 2834 0.2614 trial
44 106 0.2603 training
45 102 0.2490 purpose
46 1444 0.2485 cohort
47 659 0.2475 factor
48 1545 0.2445 association
49 109 0.2417 aim
50 209 0.2399 10
51 511 0.2352 video
52 153 0.2320 difference
53 563 0.2308 ankle
54 528 0.2307 time
55 546 0.2294 mean
56 58 0.2282 measure
57 397 0.2280 5
58 186 0.2271 design
59 108 0.2201 age
60 683 0.2197 jump
--------------------------------------------------------
Otok Petersen
- Glavna avtorja: Wolf Petersen - https://scholar.google.si/citations?user=74X8-xUAAAAJ&hl=sl&oi=sra, Thore Zantop
- Področje raziskovanja: Ortopedija, Poškodbe v športu
Rank Vertex Value Id
--------------------------------------------------------
1 11 0.0949 sport
2 179 0.0949 injury
3 169 0.0949 team
4 80 0.0949 study
5 9 0.0949 handball
6 591 0.0949 prevention
7 575 0.0843 knee
8 517 0.0832 mechanism
9 773 0.0824 ligament
10 265 0.0756 athlete
11 683 0.0724 jump
12 245 0.0715 non
13 59 0.0715 player
14 106 0.0715 training
15 755 0.0715 cruciate
16 1166 0.0715 acl
17 220 0.0674 conclusion
18 563 0.0649 ankle
19 110 0.0632 contact
20 927 0.0618 situation
21 230 0.0599 female
22 455 0.0599 program
23 767 0.0599 anterior
24 61 0.0549 result
25 243 0.0549 method
26 1406 0.0539 reduce
27 109 0.0538 aim
28 340 0.0538 soccer
29 71 0.0527 1
30 1139 0.0522 incidence
31 580 0.0522 2
32 1147 0.0516 rupture
33 788 0.0504 occur
34 594 0.0499 risk
35 426 0.0487 ball
36 1441 0.0479 prospective
37 221 0.0442 control
38 287 0.0437 use
39 607 0.0436 report
40 278 0.0435 high
41 176 0.0426 injure
42 318 0.0426 rate
43 1419 0.0420 severe
44 1524 0.0419 foot
45 251 0.0418 lower
46 425 0.0417 european
47 29 0.0408 include
48 300 0.0405 exercise
49 1577 0.0399 frequent
50 532 0.0391 joint
51 1086 0.0387 demonstrate
52 351 0.0384 position
53 91 0.0384 specific
54 502 0.0382 prevent
55 1303 0.0379 case
56 391 0.0377 male
57 4227 0.0377 landing
58 1077 0.0354 season
59 85 0.0351 muscle
60 555 0.0333 neuromuscular
--------------------------------------------------------