Open AccessCommunication Centrality in Dynamic Networks Using Time-Ordered Weighted Graph
Author(s) -
Ali Meligy,
Hani M. Ibrahem,
Ebtesam A. Othman
Publication year - 2014
Publication title -
international journal of computer network and information security
Language(s) - English
Resource type - Journals
eISSN - 2074-9104
pISSN - 2074-9090
DOI - 10.5815/ijcnis.2014.12.03
Subject(s) - centrality , computer science , graph , node (physics) , construct (python library) , representation (politics) , measure (data warehouse) , dynamic network analysis , theoretical computer science , katz centrality , topology (electrical circuits) , network analysis , betweenness centrality , network theory , data mining , mathematics , computer network , combinatorics , law , engineering , quantum mechanics , political science , politics , physics , structural engineering
Centrality is an important concept in the study of social network analysis (SNA), which is used to measure the importance of a node in a network. While many different centrality measures exist, most of them are proposed and applied to static networks. However, most types of networks are dynamic that their topology changes over time. A popular approach to represent such networks is to construct a sequence of time windows with a single aggregated static graph that aggregates all edges observed over some time period. In this paper, an approach which overcomes the limitation of this representation is proposed based on the notion of the time-ordered graph, to measure the communication centrality of a node in dynamic networks.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom