Events

Public defence in Computer Science, D.Sc. (Mil) Vesa Kuikka

Modelling Influence Spreading on Complex Networks
This network contains co-occurrences of characters in Victor Hugo's novel 'Les Misérables'. A node represents a character and an edge between two nodes shows that these two characters appeared in the same chapter of the book.

Title of the doctoral thesis: Modelling Influence Spreading on Complex Networks

Opponent: Professor Martin Rosvall, Umeå university, Sweden
Custos: Professor (emer.) Kimmo Kaski, Aalto University School of Science, Department of Computer Science

The public defence will be organised on campus.

The thesis is publicly displayed 10 days before the defence in the publication archive Aaltodoc of Aalto University

Electronic thesis

Public defence announcement:

Network Science is a growing field of research, and it has gained a lot of interest in many areas of applications. One definition of network science is the study of network representations of physical, biological, and social phenomena aiming at predictive models for them.

I propose a new influence spreading model that can be used in various applications to study different spreading processes in network structures. Applications cover describing influence spreading and community formation in social networks, information transfer in communication networks, transportation in infrastructure networks and epidemic spreading in populations. The model is based on detailed network structures of nodes, links and paths in the network. Individual node and link weights are interpreted as probabilities of transferring information, influence or infection over nodes and via links, respectively.

Detailed level descriptions of the network and its elements are needed in calculating various centrality measures for network elements and objective functions for community formation. The goal is to develop a common framework with consistent mathematical concepts, metrics and methods. All the proposed models and measures are based on probabilistic quantities and thus have physical interpretations.

Contact details of the doctoral student: [email protected], 0299 550 870

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