Hierarchical sequencing of online social graphs
Apstrakt
In online communications, patterns of conduct of individual actors and use of emotions in the process can lead to a complex social graph exhibiting multilayered structure and meso-scopic communities. Using simplicial complexes representation of graphs, we investigate in-depth topology of the online social network constructed from MySpace dialogs which exhibits original community structure. A simulation of emotion spreading in this network leads to the identification of two emotion-propagating layers. Three topological measures are introduced, referred to as the structure vectors, which quantify graphs architecture at different dimension levels. Notably, structures emerging through shared links, triangles and tetrahedral faces, frequently occur and range from tree-like to maximal 5-cliques and their respective complexes. On the other hand, the structures which spread only negative or only positive emotion messages appear to have much simpler topology consisting of links and triangles. T...he nodes structure vector represents the number of simplices at each topology level in which the node resides and the total number of such simplices determines what we define as the nodes topological dimension. The presented results suggest that the nodes topological dimension provides a suitable measure of the social capital which measures the actors ability to act as a broker in compact communities, the so called Simmelian brokerage. We also generalize the results to a wider class of computer-generated networks. Investigating components of the nodes vector over network layers reveals that same nodes develop different socio-emotional relations and that the influential nodes build social capital by combining their connections in different layers. (C) 2015 Elsevier B.V. All rights reserved.
Ključne reči:
Multiplex networks / Simplicial complexes / Online social networks / Simmelian brokerageIzvor:
Physica A: Statistical Mechanics and Its Applications, 2015, 436, 582-595Finansiranje / projekti:
- Napredne analitičke, numeričke i metode analize primenjene mehanike fluida i kompleksnih sistema (RS-174014)
- Research Agency of the Republic of Slovenia [P1-0044], European Communitys COST Action [TD1210 KNOWeSCAPE]
DOI: 10.1016/j.physa.2015.05.075
ISSN: 0378-4371; 1873-2119
WoS: 000357704500053
Scopus: 2-s2.0-84930965637
Kolekcije
Institucija/grupa
VinčaTY - JOUR AU - Anđelković, Miroslav AU - Tadić, Bosiljka AU - Maletić, Slobodan AU - Rajković, Milan PY - 2015 UR - https://vinar.vin.bg.ac.rs/handle/123456789/648 AB - In online communications, patterns of conduct of individual actors and use of emotions in the process can lead to a complex social graph exhibiting multilayered structure and meso-scopic communities. Using simplicial complexes representation of graphs, we investigate in-depth topology of the online social network constructed from MySpace dialogs which exhibits original community structure. A simulation of emotion spreading in this network leads to the identification of two emotion-propagating layers. Three topological measures are introduced, referred to as the structure vectors, which quantify graphs architecture at different dimension levels. Notably, structures emerging through shared links, triangles and tetrahedral faces, frequently occur and range from tree-like to maximal 5-cliques and their respective complexes. On the other hand, the structures which spread only negative or only positive emotion messages appear to have much simpler topology consisting of links and triangles. The nodes structure vector represents the number of simplices at each topology level in which the node resides and the total number of such simplices determines what we define as the nodes topological dimension. The presented results suggest that the nodes topological dimension provides a suitable measure of the social capital which measures the actors ability to act as a broker in compact communities, the so called Simmelian brokerage. We also generalize the results to a wider class of computer-generated networks. Investigating components of the nodes vector over network layers reveals that same nodes develop different socio-emotional relations and that the influential nodes build social capital by combining their connections in different layers. (C) 2015 Elsevier B.V. All rights reserved. T2 - Physica A: Statistical Mechanics and Its Applications T1 - Hierarchical sequencing of online social graphs VL - 436 SP - 582 EP - 595 DO - 10.1016/j.physa.2015.05.075 ER -
@article{ author = "Anđelković, Miroslav and Tadić, Bosiljka and Maletić, Slobodan and Rajković, Milan", year = "2015", abstract = "In online communications, patterns of conduct of individual actors and use of emotions in the process can lead to a complex social graph exhibiting multilayered structure and meso-scopic communities. Using simplicial complexes representation of graphs, we investigate in-depth topology of the online social network constructed from MySpace dialogs which exhibits original community structure. A simulation of emotion spreading in this network leads to the identification of two emotion-propagating layers. Three topological measures are introduced, referred to as the structure vectors, which quantify graphs architecture at different dimension levels. Notably, structures emerging through shared links, triangles and tetrahedral faces, frequently occur and range from tree-like to maximal 5-cliques and their respective complexes. On the other hand, the structures which spread only negative or only positive emotion messages appear to have much simpler topology consisting of links and triangles. The nodes structure vector represents the number of simplices at each topology level in which the node resides and the total number of such simplices determines what we define as the nodes topological dimension. The presented results suggest that the nodes topological dimension provides a suitable measure of the social capital which measures the actors ability to act as a broker in compact communities, the so called Simmelian brokerage. We also generalize the results to a wider class of computer-generated networks. Investigating components of the nodes vector over network layers reveals that same nodes develop different socio-emotional relations and that the influential nodes build social capital by combining their connections in different layers. (C) 2015 Elsevier B.V. All rights reserved.", journal = "Physica A: Statistical Mechanics and Its Applications", title = "Hierarchical sequencing of online social graphs", volume = "436", pages = "582-595", doi = "10.1016/j.physa.2015.05.075" }
Anđelković, M., Tadić, B., Maletić, S.,& Rajković, M.. (2015). Hierarchical sequencing of online social graphs. in Physica A: Statistical Mechanics and Its Applications, 436, 582-595. https://doi.org/10.1016/j.physa.2015.05.075
Anđelković M, Tadić B, Maletić S, Rajković M. Hierarchical sequencing of online social graphs. in Physica A: Statistical Mechanics and Its Applications. 2015;436:582-595. doi:10.1016/j.physa.2015.05.075 .
Anđelković, Miroslav, Tadić, Bosiljka, Maletić, Slobodan, Rajković, Milan, "Hierarchical sequencing of online social graphs" in Physica A: Statistical Mechanics and Its Applications, 436 (2015):582-595, https://doi.org/10.1016/j.physa.2015.05.075 . .