Table 1.
Definitions of social network analysis terms used in the study on trade networks through live pig markets in Guangdong Province
| Parameter | Definition |
|---|---|
| General terms | |
| Node | A node refers to a unit of interest in a network (Dube et al., 2009). In this study, supply counties and traders (sale pens in markets) are nodes in trade networks. |
| Edge | An edge represents a contact between individuals in the susceptible Population (Shirley & Rushton, 2005). In this study, counties were supplying pigs to a pen (2‐mode network), or two counties were connected by the same trader(s). Links between a county and a pen (2‐mode network) or between counties (1‐mode network) were taken as an edge. |
| Weight of links | In the bipartite network of counties and pens, the weight of a link was defined as the number of batches between a county and a pen, during a defined period. When projected as a 1‐mode network of counties, the weight of a link was defined as the total number of paths (through pens) between two source counties, during a defined period. |
| Edge density | A value reflecting the density of the network and can be calculated using equation: L/k(k − 1). L means the number of exiting edges, and k means the number of nodes in a network (Wasserman & Faust, 1994) |
| Diameter | The longest geodesic between any pair of nodes in the network (Wasserman & Faust, 1994) |
| Average path length | For any two given nodes, the shortest path between them over the paths between all pairs of nodes in the network (Dube et al., 2009) |
| Measures of centrality | |
| Degree | This parameter was calculated for the 1‐mode network of source counties. It represents the total number of contacts of a county to other counties in the network. A higher degree means more connection to other nodes in the network (Marquetoux et al., 2016). |
| Betweenness | The frequency by which a node falls between pairs of other nodes on the shortest path connecting them (Dube et al., 2009). Betweenness is a measure of centrality used to quantify a node's potential to ‘control’ the flow or curtail paths within a network (Marquetoux et al., 2016). |
| Closeness | The sum of the shortest distances (not geographical, but path length) from a source livestock operation to all other reachable operations in the network (Shirley & Rushton, 2005) |
| Measures of cohesion | |
| Clustering coefficient | This parameter was calculated for the 1‐mode network of source counties. It represents the proportion of one county's neighbours who are also neighbours to another (Watts & Strogatz, 1998). |
| Giant weakly connected component (GWCC) | The weakly connected component is the undirected subgraph in which all nodes are linked, not taking into account the direction of the links (Robinson & Christley, 2007). GWCC is the largest weak component in the network (Dube et al., 2009). In this study, the network among source counties was considered as an undirected network, so we use GWCC as the indicator for the potential magnitude of an epidemic. |