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Paolo Boldi

Dados Biográficos

ID1757599
NOMEPaolo Boldi
PRENOMESPaolo
SOBRENOMEBoldi
ASSINATURABOLDI P
AFILIAÇÕESUniversity of Milan
ORCID0000-0002-8297-6255
VERIFICADOSim
TOTAL DE OBRAS4
TOTAL DE CITAÇÕES7
TOTAL COMO AUTOR4
TOTAL COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2013
ANO MAIS RECENTE DE PUBLICAÇÃO2024
ÍNDICE H2
  • Score and rank semi-monotonicity for closeness, betweenness, and distance–decay centralities

    Open Access•Paolo Boldi, Davide D’Ascenzo et al.•ARTICLE•Social Network Analysis and Mining•2024

    Among the properties describing the behavior of centrality measures with respect to network modifications, score monotonicity means that adding an arc increases the centrality score of the target of the arc; rank monotonicity means that adding an arc improves the importance of the target with respect to the remaining nodes. It is known (Boldi and Vigna Intern Math 10:222–262, 2014, Boldi et al. Netw Sci 5(4):529–550, 2017) that score and rank mon…

  • Monotonicity in undirected networks

    Open Access•Paolo Boldi, Flavio Furia et al.•ARTICLE•Network Science•2023•Citada por: 1•Referências: 5

    Is it always beneficial to create a new relationship (have a new follower/friend) in a social network? This question can be formally stated as a property of the centrality measure that defines the importance of the actors of the network. Score monotonicity means that adding an arc increases the centrality score of the target of the arc; rank monotonicity means that adding an arc improves the importance of the target of the arc relatively to the r…

  • Rank monotonicity in centrality measures

    Open Access•Paolo Boldi, Alessandro Luongo et al.•ARTICLE•Network Science•2017•Citada por: 3•Referências: 9

    A measure of centrality is rank monotone if after adding an arc x → y , all nodes with a score smaller than (or equal to) y have still a score smaller than (or equal to) y . If, in particular, all nodes with a score smaller than or equal to y get a score smaller than y (i.e., all ties with y are broken in favor of y ), the measure is called strictly rank monotone . We prove that harmonic centrality is strictly rank monotone, whereas closeness is …

  • Robustness of social and web graphs to node removal

    Open Access•Paolo Boldi, Marco Rosa et al.•ARTICLE•Social Network Analysis and Mining•2013•Citada por: 3•Referências: 28

  • Rank monotonicity in centrality measures

    Open Access•Paolo Boldi, Alessandro Luongo et al.•ARTICLE•Network Science•2017•Citada por: 3•Referências: 9

    A measure of centrality is rank monotone if after adding an arc x → y , all nodes with a score smaller than (or equal to) y have still a score smaller than (or equal to) y . If, in particular, all nodes with a score smaller than or equal to y get a score smaller than y (i.e., all ties with y are broken in favor of y ), the measure is called strictly rank monotone . We prove that harmonic centrality is strictly rank monotone, whereas closeness is …

  • Robustness of social and web graphs to node removal

    Open Access•Paolo Boldi, Marco Rosa et al.•ARTICLE•Social Network Analysis and Mining•2013•Citada por: 3•Referências: 28

  • Monotonicity in undirected networks

    Open Access•Paolo Boldi, Flavio Furia et al.•ARTICLE•Network Science•2023•Citada por: 1•Referências: 5

    Is it always beneficial to create a new relationship (have a new follower/friend) in a social network? This question can be formally stated as a property of the centrality measure that defines the importance of the actors of the network. Score monotonicity means that adding an arc increases the centrality score of the target of the arc; rank monotonicity means that adding an arc improves the importance of the target of the arc relatively to the r…

  • Robustness of social and web graphs to node removal

    Open Access•Paolo Boldi, Marco Rosa et al.•ARTICLE•Social Network Analysis and Mining•2013•Citada por: 3•Referências: 28

  • Rank monotonicity in centrality measures

    Open Access•Paolo Boldi, Alessandro Luongo et al.•ARTICLE•Network Science•2017•Citada por: 3•Referências: 9

    A measure of centrality is rank monotone if after adding an arc x → y , all nodes with a score smaller than (or equal to) y have still a score smaller than (or equal to) y . If, in particular, all nodes with a score smaller than or equal to y get a score smaller than y (i.e., all ties with y are broken in favor of y ), the measure is called strictly rank monotone . We prove that harmonic centrality is strictly rank monotone, whereas closeness is …

  • Monotonicity in undirected networks

    Open Access•Paolo Boldi, Flavio Furia et al.•ARTICLE•Network Science•2023•Citada por: 1•Referências: 5

    Is it always beneficial to create a new relationship (have a new follower/friend) in a social network? This question can be formally stated as a property of the centrality measure that defines the importance of the actors of the network. Score monotonicity means that adding an arc increases the centrality score of the target of the arc; rank monotonicity means that adding an arc improves the importance of the target of the arc relatively to the r…

  • Score and rank semi-monotonicity for closeness, betweenness, and distance–decay centralities

    Open Access•Paolo Boldi, Davide D’Ascenzo et al.•ARTICLE•Social Network Analysis and Mining•2024

    Among the properties describing the behavior of centrality measures with respect to network modifications, score monotonicity means that adding an arc increases the centrality score of the target of the arc; rank monotonicity means that adding an arc improves the importance of the target with respect to the remaining nodes. It is known (Boldi and Vigna Intern Math 10:222–262, 2014, Boldi et al. Netw Sci 5(4):529–550, 2017) that score and rank mon…

Complex Network Analysis Techniques (4 obras) · Computer Science (4 obras) · Betweenness centrality (3 obras) · Centrality (3 obras) · Closeness (3 obras) · Combinatorics (3 obras) · Graph theory and applications (3 obras) · Mathematics (3 obras) · Monotonic function (3 obras) · Theoretical Computer Science (3 obras)

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