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.
Network Properties
Meta-network Network Symmetric Binary Ignore Self-loops 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 Event x Location n/a False (auto-detect) n/a tanzania_3_2006 Knowledge x Task n/a False (auto-detect) n/a tanzania_3_2006 Resource x Task n/a False (auto-detect) n/a tanzania_3_2006 Agent x Agent False (auto-detect) True (auto-detect) True (auto-detect) tanzania_3_2006 Location x Location False (auto-detect) False (auto-detect) False (auto-detect) tanzania_3_2006 Location x Organization 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 Task x Task False (auto-detect) False (auto-detect) True (auto-detect) tanzania_3_2006 Agent x Belief n/a True (auto-detect) n/a tanzania_3_2006 Organization x Belief n/a True (auto-detect) n/a tanzania_3_2006 Organization x Task n/a True (auto-detect) n/a
Produced by ORA developed at CASOS - Carnegie Mellon University