Table 2.
The following leader cluster algorithm (FLCA) used in this study (matching up).
| Input k, sorting dataset (name, connections, cluster#) | |
|---|---|
| Output the final clusters | |
| 1 | Ensure k (in k, all entities having at least one follower become a leader) |
| 2 | For jk = 1 To n dataset A(size = n) |
| 3 | If jk <=k Then |
| 4 | Cluster#= dataset A.Cells(jk, 3) |
| 5 | Search for followers(with identical cluster#) |
| 6 | If found() Then |
| 7 | Dataset ACells(jk, 3) = giving the initial cluster# |
| 8 | End If |
| 9 | Else |
| 10 | Cluster#= dataset A.Cells(jk, 3) |
| 11 | For j = jk + 1 To n |
| 12 | If dateset A.Cells(j, 3) = jkThen |
| 13 | (=leader cluster#) |
| 14 | Dataset A Cells(j, 3) = cluster # |
| 15 | (=set identical cluster# with the leader cluster#) |
| 16 | End If |
| 17 | Next j end cluster# update |
| 18 | End If |
| 19 | Next jk end dataset A(size = n) |
| 20 | Renew cluster# with counts from 1 to the number of clusters |