Dimitrios Rafailidis
ABSTRACT
We propose a new link-injection method aiming at boosting the overall diffusion of information in social networks. Our approach is based on a diffusion-coverage score of the ability of each user to spread information over the network. Candidate links for injection are identified by a matrix factorization technique and link injection is performed by attaching links to users according to their score. We additionally perform clustering to identify communities in order to inject links that cross the boundaries of such communities. In our experiments with five real world networks, we demonstrate that our method can significantly spread the information diffusion by performing limited link injection, essential to real-world applications
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Index Terms
- Crossing the Boundaries of Communities via Limited Link Injection for Information Diffusion In Social Networks
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