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Authors: Flora Amato ; Antonio Bosco ; Vincenzo Moscato ; Antonio Picariello and Giancarlo Sperlí

Affiliation: University of Naples “Federico II” and Complesso Universitario Monte Santangelo, Italy

Keyword(s): Multimedia Social Network, Influence Analysis, Big Data.

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.

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Paper citation in several formats:
Amato, F.; Bosco, A.; Moscato, V.; Picariello, A. and Sperlí, G. (2017). A Novel Influence Diffusion Model based on User Generated Content in Online Social Networks. In Proceedings of the 6th International Conference on Data Science, Technology and Applications - KomIS; ISBN 978-989-758-255-4; ISSN 2184-285X, SciTePress, pages 314-320. DOI: 10.5220/0006486703140320

@conference{komis17,
author={Flora Amato. and Antonio Bosco. and Vincenzo Moscato. and Antonio Picariello. and Giancarlo Sperlí.},
title={A Novel Influence Diffusion Model based on User Generated Content in Online Social Networks},
booktitle={Proceedings of the 6th International Conference on Data Science, Technology and Applications - KomIS},
year={2017},
pages={314-320},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006486703140320},
isbn={978-989-758-255-4},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Data Science, Technology and Applications - KomIS
TI - A Novel Influence Diffusion Model based on User Generated Content in Online Social Networks
SN - 978-989-758-255-4
IS - 2184-285X
AU - Amato, F.
AU - Bosco, A.
AU - Moscato, V.
AU - Picariello, A.
AU - Sperlí, G.
PY - 2017
SP - 314
EP - 320
DO - 10.5220/0006486703140320
PB - SciTePress

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