1. A Novel Influence Diffusion Model based on User Generated Content in Online Social Networks
- Author
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Antonio Picariello, Antonio Bosco, Giancarlo Sperlì, Flora Amato, Vincenzo Moscato, Quix C.,Joaquim J.,Joaquim J.,Bernardino J.,Quix C., Amato, Flora, Bosco, Antonio, Moscato, Vincenzo, Picariello, Antonio, and Sperli', Giancarlo
- Subjects
World Wide Web ,Multimedia ,Computer science ,0202 electrical engineering, electronic engineering, information engineering ,User-generated content ,Big data, Influence analysis, Multimedia social network ,020206 networking & telecommunications ,020201 artificial intelligence & image processing ,02 engineering and technology ,computer.software_genre ,computer - Abstract
Social Network Analysis has been introduced to study the properties of Online Social Networks for a wide range of real life applications. In this paper, we propose a novel methodology for solving the Influence Maximization problem, i.e. the problem of finding a small subset of actors in a social network that could maximize the spread of influence. In particular, we define a novel influence diffusion model that, learning recurrent user behaviours from past logs, estimates the probability that a given user can influence the other ones, basically exploiting user to content actions. A greedy maximization algorithm is then adopted to determine the final set of influentials in the network. Preliminary experimental results shows the goodness of the proposed approach, especially in terms of efficiency, and encourage future research in such direction.
- Published
- 2017
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