TY - GEN
T1 - Reliability model for inuencing individuals in the social network setting
AU - Ramirez-Marquez, J. E.
AU - Hernandez, Ivan
AU - Schneider, Kellie
AU - Raintwater, Chase
AU - Pohl, Edward A.
PY - 2012
Y1 - 2012
N2 - Social networks have proven to be useful in describing the interactions among individuals in numerous social, professional and military contexts. Recently, researchers have shown increased in- terest in the quantitative study of social networks to determine the most critical members of networks. However, most of the work done at this point is restricted to a binary context (i.e. communication either exists or not among individuals) without any inclusion of reliability considerations. This paper considers a social network in which actors have the ability to provide some level of influence over other actors within the network in a probabilistic manner. The necessary model paradigms to evaluate the influence exchange and propagation in the network are developed. Specifically, the manuscript implements the concept of probabilistic actor influence and influence synergy. A Monte Carlo (MC) simulation model is developed to evaluate and quantify how influence is exchanged and propagated throughout the network. The MC results are then analyzed using two high level performance metrics. Specifically, we consider a general organization level influence model which focuses on analyzing the ex- pected influence level across actors within the network, and also targeted actor influence model which describes the probability of influencing specific network actors (equivalent to 2-terminal reliability). These approaches borrow from and complement theory developed in multi-state network reliability to describe probabilistically the influence of individuals in affecting network outcomes. Finally, we present an illustrative example using both a traditional, centrality-based social network analysis, and the new multi-state influence model with associated performance metrics.
AB - Social networks have proven to be useful in describing the interactions among individuals in numerous social, professional and military contexts. Recently, researchers have shown increased in- terest in the quantitative study of social networks to determine the most critical members of networks. However, most of the work done at this point is restricted to a binary context (i.e. communication either exists or not among individuals) without any inclusion of reliability considerations. This paper considers a social network in which actors have the ability to provide some level of influence over other actors within the network in a probabilistic manner. The necessary model paradigms to evaluate the influence exchange and propagation in the network are developed. Specifically, the manuscript implements the concept of probabilistic actor influence and influence synergy. A Monte Carlo (MC) simulation model is developed to evaluate and quantify how influence is exchanged and propagated throughout the network. The MC results are then analyzed using two high level performance metrics. Specifically, we consider a general organization level influence model which focuses on analyzing the ex- pected influence level across actors within the network, and also targeted actor influence model which describes the probability of influencing specific network actors (equivalent to 2-terminal reliability). These approaches borrow from and complement theory developed in multi-state network reliability to describe probabilistically the influence of individuals in affecting network outcomes. Finally, we present an illustrative example using both a traditional, centrality-based social network analysis, and the new multi-state influence model with associated performance metrics.
KW - Influence
KW - Multi-state
KW - Social networks
KW - Terminal reliability
UR - http://www.scopus.com/inward/record.url?scp=84873140280&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84873140280&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84873140280
SN - 9781622764365
T3 - 11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012, PSAM11 ESREL 2012
SP - 4602
EP - 4611
BT - 11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012, PSAM11 ESREL 2012
T2 - 11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012, PSAM11 ESREL 2012
Y2 - 25 June 2012 through 29 June 2012
ER -