This page contains a description of the transformations and settings for each network prior to calculating measures. Auto-detect means that the network was not modified, but only measured to determine whether each property is true or false. Note that symmetry and self-loops only apply to uni-modal networks. These settings affect measure values.

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Network Properties

Meta-network	Network	Symmetric	Binary	Ignore Self-loops
tanzania_3_2006	agent x agent	False (auto-detect)	True (auto-detect)	True (auto-detect)
tanzania_3_2006	agent x belief	n/a	False (auto-detect)	n/a
tanzania_3_2006	agent x event	n/a	False (auto-detect)	n/a
tanzania_3_2006	agent x knowledge	n/a	True (auto-detect)	n/a
tanzania_3_2006	agent x location	n/a	False (auto-detect)	n/a
tanzania_3_2006	agent x organization	n/a	False (auto-detect)	n/a
tanzania_3_2006	agent x resource	n/a	True (auto-detect)	n/a
tanzania_3_2006	agent x task	n/a	False (auto-detect)	n/a
tanzania_3_2006	belief x task	n/a	True (auto-detect)	n/a
tanzania_3_2006	event x location	n/a	False (auto-detect)	n/a
tanzania_3_2006	knowledge x belief	n/a	False (auto-detect)	n/a
tanzania_3_2006	knowledge x task	n/a	False (auto-detect)	n/a
tanzania_3_2006	location x location	False (auto-detect)	False (auto-detect)	False (auto-detect)
tanzania_3_2006	organization x location	n/a	True (auto-detect)	n/a
tanzania_3_2006	resource x resource	True (auto-detect)	True (auto-detect)	True (auto-detect)
tanzania_3_2006	resource x task	n/a	False (auto-detect)	n/a
tanzania_3_2006	task x task	False (auto-detect)	False (auto-detect)	True (auto-detect)

Produced by ORA developed at CASOS - Carnegie Mellon University