A key assumption of Granovetter’s (1973) Strength of Weak Ties theory is that strong ties are embedded by being part of triangles, whereas weak ties are not embedded by being created towards disconnected nodes. This assumption have been tested by calculating the traditional clustering coefficient on binary networks created with increasing cut-off parameters (i.e., creating […]| Tore Opsahl
This post highlights a generalisation of Freeman’s (1978) betweenness measure to weighted networks implicitly introduced by Brandes (2001) when he developed an algorithm for calculating betweenness faster. Betweenness is a measure of the extent to which a node funnels transactions among all the other nodes in the network. By funnelling the transactions, a node can […]| Tore Opsahl
The method used to operationalise ties’ strength into weights affects the outcomes of weighted networks measures. Simply assigning 1, 2, and 3 to three different levels of tie strength might not be appropriate as this scale might misrepresent the actually difference among the three levels (using an ordinal scale). In this post, I highlight issues […]| Tore Opsahl
The generalisation of the local clustering coefficient to weighted networks by Barrat et al. (2004) considers the value of a triplet to be the average of the weights attached to the two ties that make up the triplet. In this post, I suggest three additional methods for defining the triplet value. The content […]| Tore Opsahl
The average distance that separate nodes in a network became a famous measure following Milgram’s six-degrees of separation experiment in 1967 that found that people in the US were on average…| Tore Opsahl
This post proposes a local (node-level) version of the Weighted Rich-club Effect (PRL 101, 168702). By incorporating this measure into a regression analysis, the impact of targeting efforts towards…| Tore Opsahl