TY - GEN
T1 - Red black network
T2 - 2013 IEEE Military Communications Conference, MILCOM 2013
AU - Pandit, Saurav
AU - Koch, Jonathan
AU - Yang, Yang
AU - Uzzi, Brian
AU - Chawla, Nitesh V.
PY - 2013
Y1 - 2013
N2 - In this paper we introduce and study the properties of certain kind of interdependent networks that we collectively call a Red Black Network - two intertwined social networks that work together towards a series of events (missions or performances). More specifically, members of one of the two networks is responsible for planning and organizing the events. They will generally be referred to as artists. Members of the other network, henceforth called actors, are responsible for the execution of the events. Using temporal data from the performing arts industry, we study the co-evolution of two such co-dependent social networks. We find that the statistical properties of two such networks are highly correlated, and use that finding to devise a prediction mechanism for such properties in a scenario when one of the two networks is invisible or only partially visible. This also sets up a framework for our ultimate goal of temporal, semi-blind, multi-relational link prediction.
AB - In this paper we introduce and study the properties of certain kind of interdependent networks that we collectively call a Red Black Network - two intertwined social networks that work together towards a series of events (missions or performances). More specifically, members of one of the two networks is responsible for planning and organizing the events. They will generally be referred to as artists. Members of the other network, henceforth called actors, are responsible for the execution of the events. Using temporal data from the performing arts industry, we study the co-evolution of two such co-dependent social networks. We find that the statistical properties of two such networks are highly correlated, and use that finding to devise a prediction mechanism for such properties in a scenario when one of the two networks is invisible or only partially visible. This also sets up a framework for our ultimate goal of temporal, semi-blind, multi-relational link prediction.
UR - http://www.scopus.com/inward/record.url?scp=84897730008&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84897730008&partnerID=8YFLogxK
U2 - 10.1109/MILCOM.2013.128
DO - 10.1109/MILCOM.2013.128
M3 - Conference contribution
AN - SCOPUS:84897730008
SN - 9780769551241
T3 - Proceedings - IEEE Military Communications Conference MILCOM
SP - 719
EP - 724
BT - Proceedings - 2013 IEEE Military Communications Conference, MILCOM 2013
Y2 - 18 November 2013 through 20 November 2013
ER -