Contents
- Index

**DATA>CSS**

**PURPOSE **Combines a number of different relations or cognitive "slices" of the same network into a single pooled network. These may either be a number of views of the whole network or the view of the whole network through all ego centered networks.

**DESCRIPTION **The input is a set of k adjacency matrices, each of the form A(i,j) stacked into a three-dimensional matrix, A(i,j,k). This form is useful for cognitive social structures, where k refers to the perceiver of a relation from i to j. This routine compresses this 3-D matrix into a two-dimensional matrix, A'(i,j) using one of two methods. One is to compute the element-wise sum over the k matrices: A'(i,j) = SUM over k of A(i,j,k) This matrix can be dichotomized around a threshold to produce a "consensus" structure.

Alternatively, one can produce a "locally aggregated structure" (LAS) by setting A'(i,j) = A(i,j,i)+A(i,j,j). In other words, the value of a given cell in the aggregate matrix is a function only of the perceptions of the two individuals involved, not the whole group. This matrix can also be dichotomized.

**PARAMETERS**

** Input dataset:**

Name of file containing any set of matrices representing the same network. Data type: Valued graph. Multirelational.

* ***Method of Pooling graphs (Default = Slice)**

Choices are:

**Slice. **Take an individuals view of the network. This simply extracts a single matrix from the structure.

** **

** ****Row LAS. **Construct a matrix which uses each respondents row as a row in the data matrix. The result is that each row of the data corresponds to the respondents perception of that row.

** ****Column LAS. **Construct a matrix which uses each respondents column as a column in the data matrix. The result is that each column of the data corresponds to the respondents perception of that column.

** ****Intersection LAS. **Construct a matrix with a connection between i and j if both i and j agree that such a connection exists.

** ****Union LAS. **Construct a matrix with a connection between i and j if either i or j state that such a connection exists.

** ****Median LAS. **Construct a matrix with values A(i,j) which are the median of i's value of the i,j connection and j's value of the connection.

** ****Consensus. **The consensus takes the sum of all the respondents and then dichotomizes the sum.

** ****Average. **The average of all the respondents view of the network.

If the users choose either Slice or Consensus then the following parameters will be highlighted.

**(For Slice Method) Which informants slice?** (Default = 1)

Number of actor to be the informant

**(For consensus method) Threshold value** (Default =0.5)

Threshold value for dichotomizing the aggregated matrix.

* *

* ***Output dataset** (Default = 'Pooled')

Output file that will contain pooled graph .

**LOG FILE **Pooled graph adjacency matrix.

**TIMING** O(N^2)

**COMMENTS** None.

**REFERENCES **Krackhardt D. (1987). 'Cognitive social structures'. Social Networks 9, 104-134.