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Influencing busy people in a social network
Kaushik Sarkar,
Hari Sundaram
Charles H. Sandage Department of Advertising
Institute of Communications Research
Center for Social & Behavioral Science
Siebel School of Computing and Data Science
Research output
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peer-review
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Keyphrases
Social Networks
100%
Early Adopters
66%
Greedy Algorithm
33%
Nave
33%
NP-hard
33%
Large-scale Networks
33%
Behavioral Activity
33%
Collective Behavior
33%
Number of Participants
33%
Behavioural Influences
33%
Multiple Behaviors
33%
Resource Utilization
33%
Resource Constraints
33%
Active Networks
33%
Resource-constrained
33%
Efficient Heuristics
33%
Influential Individuals
33%
Network Resource Utilization
33%
Influence Maximization
33%
Viral Marketing
33%
Unique number
33%
Action Constraints
33%
Computer Science
Social Network
100%
Resource Utilisation
66%
Network Resource
33%
Resource Constraint
33%
World Topology
33%
Greedy Algorithm
33%