TY - GEN
T1 - Second-Order Assortative Mixing in Social Networks
AU - Zhou, Shi
AU - Cox, Ingemar
AU - Hansen, Lars Kai
PY - 2017
Y1 - 2017
N2 - In a social network, the number of links of a node, or node degree, is often assumed as a proxy for the node’s importance or prominence within the network. It is known that social networks exhibit the (first-order) assortative mixing, i.e. if two nodes are connected, they tend to have
similar node degrees, suggesting that people tend to mix with those of comparable prominence. In this paper, we report the second-order assortative mixing in social networks. If two nodes are connected, we measure the degree correlation between their most prominent neighbours, rather than between
the two nodes themselves. We observe very strong second-order assortative mixing in social networks, often significantly stronger than the first-order assortative mixing. This suggests that if two people interact in a social network, then the importance of the most prominent person each knows is very likely to be the same. This is also true if we measure the average prominence of neighbours of the two people. This property is weaker or negative in non-social networks. We investigate a number of possible
explanations for this property. However, none of them was found to provide an adequate explanation. We therefore conclude that second-order assortative mixing is a new property of social networks.
AB - In a social network, the number of links of a node, or node degree, is often assumed as a proxy for the node’s importance or prominence within the network. It is known that social networks exhibit the (first-order) assortative mixing, i.e. if two nodes are connected, they tend to have
similar node degrees, suggesting that people tend to mix with those of comparable prominence. In this paper, we report the second-order assortative mixing in social networks. If two nodes are connected, we measure the degree correlation between their most prominent neighbours, rather than between
the two nodes themselves. We observe very strong second-order assortative mixing in social networks, often significantly stronger than the first-order assortative mixing. This suggests that if two people interact in a social network, then the importance of the most prominent person each knows is very likely to be the same. This is also true if we measure the average prominence of neighbours of the two people. This property is weaker or negative in non-social networks. We investigate a number of possible
explanations for this property. However, none of them was found to provide an adequate explanation. We therefore conclude that second-order assortative mixing is a new property of social networks.
KW - Physics
KW - Applications of Graph Theory and Complex Networks
KW - Computational Social Sciences
KW - Computational Intelligence
KW - Artificial Intelligence (incl. Robotics)
KW - Complexity
U2 - 10.1007/978-3-319-54241-6_1
DO - 10.1007/978-3-319-54241-6_1
M3 - Article in proceedings
SN - 9783319542416
T3 - Springer Proceedings in Complexity
SP - 3
EP - 15
BT - Complex Networks Viii
PB - Springer
T2 - 8th Conference on Complex Networks Complenet 2017
Y2 - 21 March 2017 through 24 March 2017
ER -