Simple relational networks benefit from transitivity: friends of friends are more likely to know each other. Signed sentiment networks do not: the enemy of my

Simple relational networks benefit from transitivity: friends of friends are more likely to know each other. Signed sentiment networks do not: the enemy of my enemy is not always my friend. And things get even more complicated when you want to reason along paths where the edges have a deep taxonomy: if paper A disagrees with paper B, and paper B views C as foundational, can we say anything about A -> C? This is a deep problem because real networks are rarely fully observed. Even if you can accurately map all citations, you are not observing all the opinion relations with which you would be labeling the edges. Most network analysis methods lean heavily on simple, transitive relations that diffuse information over paths, in part because it helps compensate for missing and noisy data. Interestingly, taking signed networks and treating them as simple relational networks often yields useful predictive results. Hate is not the opposite of love! Squishing both into a "feels strongly about" can't answer all the same questions, but it can answer some interesting ones.