Opinion formation models in static and dynamic social networks
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Authors
Singh, Pramesh
Issue Date
2014-08
Type
Electronic thesis
Thesis
Thesis
Language
ENG
Keywords
Physics
Alternative Title
Abstract
In the first model that we study on a static network, a node adopts a particular state (opinion) if a threshold fraction of its neighbors are already in that state. We introduce a few initiator nodes which are in state ‘1’ in a population where every node is in state ‘0’. Thus, opinion ‘1’ spreads through the population until no further influence is possible. Size of the spread is greatly affected by how these initiator nodes are selected. We find that there exists a critical fraction of initiators pc that is needed to trigger global cascades for a given threshold φ. We also study heuristic strategies for selecting a set of initiator nodes in order to maximize the cascade size. The structural properties of networks also play an important role in the spreading process. We study how the dynamics is affected by changing the clustering in a network. It turns out that local clustering is helpful in spreading.
Description
August 2014
School of Science
School of Science
Full Citation
Publisher
Rensselaer Polytechnic Institute, Troy, NY