. do example.do

. * nwcommands tutorial 16: valued networks
. * Requires the core nwcommands.
. nwwebuse sampson, nwclear

. 
. * 1. A valued network: how many times was a pair named?
. nwsymmetrize samplike, generate(likes)

. nwsummarize likes
--------------------------------------------------
   Network name:  likes
   Network id:  5
   Directed: false
   Valued: true
   Two-mode: false
   Nodes: 18
   Selfloop: false
   Edges: 60
   Minimum value:  0
   Maximum value:  3
   Density:  .392
   Temporal: false

. 
. * 2. A network from an edge list with a value variable
. clear

. input str5 ego str5 alter int mails

           ego      alter     mails
  1. "Ann" "Bob" 12
  2. "Ann" "Cy"   1
  3. "Bob" "Cy"   5
  4. "Cy"  "Dee"  2
  5. "Dee" "Ann"  7
  6. end

. nwfromedge ego alter mails, name(mailnet) directed

. nwsummarize mailnet
--------------------------------------------------
   Network name:  mailnet
   Network id:  6
   Directed: true
   Valued: true
   Two-mode: false
   Nodes: 4
   Selfloop: false
   Arcs: 5
   Minimum value:  0
   Maximum value:  12
   Density:  .417
   Temporal: false

. 
. * 3. Degree is strength for a valued network
. nwwebuse sampson, nwclear

. nwsymmetrize samplike, generate(likes)

. nwdegree likes, generate(strength)
----------------------------------------
  Network name: likes
----------------------------------------
  (valued network: degree is the strength, the sum of the tie values; binary gives the number of tie
> s)
    Degree distribution

   strength |      Freq.     Percent        Cum.
------------+-----------------------------------
          9 |          1        5.56        5.56
         10 |          3       16.67       22.22
         11 |          2       11.11       33.33
         12 |          1        5.56       38.89
         13 |          6       33.33       72.22
         14 |          2       11.11       83.33
         18 |          1        5.56       88.89
         22 |          1        5.56       94.44
         23 |          1        5.56      100.00
------------+-----------------------------------
      Total |         18      100.00
  Mean number of ties (out): 6.667   mean strength (out): 13.44

   Degree centralization: .632

. nwdegree likes, generate(ties) binary
----------------------------------------
  Network name: likes
----------------------------------------
  (valued network, tie values not used: degree is the number of ties)
    Degree distribution

       ties |      Freq.     Percent        Cum.
------------+-----------------------------------
          4 |          1        5.56        5.56
          5 |          4       22.22       27.78
          6 |          5       27.78       55.56
          7 |          3       16.67       72.22
          8 |          3       16.67       88.89
         10 |          1        5.56       94.44
         11 |          1        5.56      100.00
------------+-----------------------------------
      Total |         18      100.00
  Mean number of ties (out): 6.667   mean strength (out): 13.44

   Degree centralization: .287

. summarize strength ties

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
    strength |         18    13.44444    3.883937          9         23
        ties |         18    6.666667     1.81497          4         11

. 
. * 4. Clustering, weighted and binary
. nwclustering likes, generate(wclu) silent

. nwclustering likes, generate(bclu) measure(binary) silent

. summarize wclu bclu

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
        wclu |         18    .5075819    .1789176       .225   .8888889
        bclu |         18    .4925926      .17616         .2   .8333333

. 
. nwbetween likes, generate(wbtw) silent
----------------------------------------
  Network name: likes
----------------------------------------
    Betweenness centrality
    (shortest paths weighted by tie values: step cost 1/value^alpha, alpha = 1)

. nwbetween likes, generate(bbtw) binary silent
----------------------------------------
  Network name: likes
----------------------------------------
    Betweenness centrality

. correlate wbtw bbtw
(obs=18)

             |     wbtw     bbtw
-------------+------------------
        wbtw |   1.0000
        bbtw |   0.7912   1.0000


. 
. * 5. Dichotomize with a cutoff
. nwdichotomize likes, threshold(2) generate(likes2)
(120 changes made to likes)

. nwsummarize likes2
--------------------------------------------------
   Network name:  likes2
   Network id:  6
   Directed: false
   Valued: false
   Two-mode: false
   Nodes: 18
   Selfloop: false
   Edges: 37
   Minimum value:  0
   Maximum value:  1
   Density:  .242
   Temporal: false

. nwdegree likes2, generate(deg2)
----------------------------------------
  Network name: likes2
----------------------------------------
    Degree distribution

       deg2 |      Freq.     Percent        Cum.
------------+-----------------------------------
          2 |          1        5.56        5.56
          3 |          5       27.78       33.33
          4 |          8       44.44       77.78
          5 |          1        5.56       83.33
          6 |          1        5.56       88.89
          7 |          2       11.11      100.00
------------+-----------------------------------
      Total |         18      100.00

   Degree centralization: .191

.