TY - GEN
T1 - Power of Nodes Based on Their Interdependence
AU - Shvydun, Sergey
PY - 2020
Y1 - 2020
N2 - Power of nodes has been studied in many works, in particular, using centrality concepts. However, in some applications, a large flow between two nodes implies that these nodes become too interdependent on each other. For instance, in trade networks, the possible shortage of flow between two countries may lead to the deficit of goods in the importing country but, on the other hand, it may also affect the financial stability of the exporting country. This feature is not captured by existing centrality measures. Thus, we propose an approach that takes into account interdependence of nodes. First, we evaluate how nodes influence and depend on each other via the same flow based on their individual attributes and a possibility of their group influence. Second, we present several models that transform information about direct influence to a single vector with respect to the network structure. Finally, we compare our models with centrality measures on artificial and real networks.
AB - Power of nodes has been studied in many works, in particular, using centrality concepts. However, in some applications, a large flow between two nodes implies that these nodes become too interdependent on each other. For instance, in trade networks, the possible shortage of flow between two countries may lead to the deficit of goods in the importing country but, on the other hand, it may also affect the financial stability of the exporting country. This feature is not captured by existing centrality measures. Thus, we propose an approach that takes into account interdependence of nodes. First, we evaluate how nodes influence and depend on each other via the same flow based on their individual attributes and a possibility of their group influence. Second, we present several models that transform information about direct influence to a single vector with respect to the network structure. Finally, we compare our models with centrality measures on artificial and real networks.
KW - Group influence
KW - Individual attributes
KW - Influence in networks
KW - Interdependence
KW - Trade networks
UR - http://www.scopus.com/inward/record.url?scp=85081200627&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-40943-2_7
DO - 10.1007/978-3-030-40943-2_7
M3 - Conference contribution
AN - SCOPUS:85081200627
SN - 9783030409425
T3 - Springer Proceedings in Complexity
SP - 70
EP - 82
BT - Complex Networks XI - Proceedings of the 11th Conference on Complex Networks, CompleNet 2020
A2 - Barbosa, Hugo
A2 - Menezes, Ronaldo
A2 - Gomez-Gardenes, Jesus
A2 - Gonçalves, Bruno
A2 - Mangioni, Giuseppe
A2 - Oliveira, Marcos
PB - Springer
T2 - 11th International Conference on Complex Networks, CompleNet 2020
Y2 - 31 March 2020 through 3 April 2020
ER -