make_projection {surveygraph}

Outputs the survey projection onto the agent or symbolic layer

Description

make_projection() outputs the agent or symbolic network corresponding to a survey, i.e. the row or column projection.

Usage

make_projection(
  data,
  layer,
  threshold_method = NULL,
  method_value = NULL,
  centre = NULL,
  similarity_metric = NULL
)

Arguments

data

A data frame corresponding to a survey

layer

A string flag specifying which layer to project

• "agent" produces the network corresponding to the agents, which we assume to be rows in data

• "symbolic" produces the network corresponding to the symbols, or items, which we assume to be columns in data

threshold_method

A string flag specifying how edges are selected in the network representation.

• "raw_similarity" means we remove all edges whose weight, meaning node similarity, is below a specified threshold.

• "target_lcc" finds the value of the threshold that results in the network whose largest connected component is as close as possible to a specified value. In general a range of thresholds will satisfy this condition, and we choose the upper limit of this range.

• "target_ad" finds the value of the threshold that results in the network whose average degree is as close as possible to a specified value.

method_value

A utility variable that we interpret according to the threshold_method chosen.

• If threshold_method = "raw_similarity", then method_value is interpreted as the similarity threshold, and thus is in the range ⁠[-1, 1]⁠. A value of -1 means no edges are removed, and a value of 1 means all edges are removed.

• If threshold_method = "target_lcc", then method_value is interpreted as the desired fractional size of the largest connected component, in the range ⁠[0, 1]⁠. E.g., when set to 0, no nodes are connected, and if set to 1, the network is as sparse as possible while remaining fully connected.

• If threshold_method = "target_ad", then method_value is interpreted as the desired average degree. We assume that method_value is normalised to the range ⁠[0, 1]⁠ When method_value = 0, then no nodes are connected, and if method_value = 1, the network is complete, meaning it contains every possible edge.

centre

If FALSE, we shift edge weights by 1 from ⁠[-1, 1]⁠ to ⁠[0, 2]⁠. Defaults to TRUE.

similarity_metric

This currently has just one allowed value, namely the Manhattan distance, which is the default.

Value

A data frame corresponding to the edge list of the specified network. It contains three columns named

• u, the first node adjacent to the edge

• v, the second node adjacent to the edge, and

• weight, the similarity between nodes u and v

Examples

S <- make_synthetic_data(20, 5)