FAQ
logo of Jagiellonian University in Krakow

Modelling Influence Propagation in Social Networks

Publication date: 11.04.2016

Schedae Informaticae, 2015, Volume 24, pp. 93 - 101

https://doi.org/10.4467/20838476SI.15.009.3031

Authors

Anna Szczepanek
Jagiellonian University in Kraków, Gołębia 24, 31-007 Kraków, Poland
All publications →

Titles

Modelling Influence Propagation in Social Networks

Abstract

This paper presents a formalised description of the models of influence propagation in social networks introduced in the classic paper of Kempe et al. The formal framework that we propose clarifies the structure of the most popular propagation models and helps rigorously re-establish the essential results concerning the problem of influence maximisation. We also introduce new models of propagation and show how they fit into the general picture. In particular, we focus on models that capture either positive or negative effects of resisting influence on individual’s future resistance.

References

[1] Kempe D., Kleinberg J., Tardos E., Maximizing the spread of influence through a social network. KDD ’03, ACM, New York, 2003.
[2] Kempe D., Kleinberg J., Tardos E., Influential nodes in a diffusion model for social networks. ICALP’05, Springer-Verlag, Berlin, 2005.
[3] Nemhauser G., Wolsey L., Fisher M., An analysis of approximations for maximizing submodular set functions I. Math. Prog., 1978, 14.
[4] Mossel E., Roch S., Submodularity of influence in social networks: From local to global. SIAM J. Comput., 2010, 39.

Information

Information: Schedae Informaticae, 2015, Volume 24, pp. 93 - 101

Article type: Original article

Titles:

Polish:

Modelling Influence Propagation in Social Networks

English:

Modelling Influence Propagation in Social Networks

Authors

Jagiellonian University in Kraków, Gołębia 24, 31-007 Kraków, Poland

Published at: 11.04.2016

Article status: Open

Licence: None

Percentage share of authors:

Anna Szczepanek (Author) - 100%

Article corrections:

-

Publication languages:

English

View count: 1984

Number of downloads: 1300

<p> Modelling Influence Propagation in Social Networks</p>