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Centrality measure in social networks based on linear threshold model

Author
Riquelme, F.; Gonzalez, P.; Molinero, X.; Serna, M.
Type of activity
Journal article
Journal
Knowledge-based systems
Date of publication
2018-01-15
Volume
140
First page
92
Last page
102
DOI
https://doi.org/10.1016/j.knosys.2017.10.029 Open in new window
Project funding
Algorísmia, Bioinformàtica, Complexitat i Mètodes Formals ALBCOM
Computational Models and Methods for Massive Structured Data
Mathematical, computational and social aspects in voting and cooperation contexts
Repository
http://hdl.handle.net/2117/111727 Open in new window
URL
http://www.sciencedirect.com/science/article/pii/S0950705117304975?via%3Dihub Open in new window
Abstract
Centrality and influence spread are two of the most studied concepts in social network analysis. In recent years, centrality measures have attracted the attention of many researchers, generating a large and varied number of new studies about social network analysis and its applications. However, as far as we know, traditional models of influence spread have not yet been exhaustively used to define centrality measures according to the influence criteria. Most of the considered work in this topic ...
Citation
Riquelme, F., Gonzalez, P., Molinero, X., Serna, M. Centrality measure in social networks based on linear threshold model. "Knowledge-based systems", 15 Gener 2018, vol. 140, p. 92-102.
Keywords
Centrality, Independent cascade model, Linear threshold model, Social network, Spread of influence
Group of research
ALBCOM - Algorithms, Computational Biology, Complexity and Formal Methods
GRTJ - Game Theory Research Group

Participants