A Novel Approach To Information Spreading Models for Social Networks

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Sayın, Burcu
Şahin, Serap

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Abstract

Analyzing and modelling the spreading of any information through a social network (SN) is an important issue in social network analysis. Proposed solutions for this issue do not only help observing the information diffusion but also serve as a valuable resource for predicting the characteristics of the network, developing network-specific advertising etc. Up-to-date approaches include probabilistic analysis of information spreading and the information cascade models. In this paper, we propose a hybrid model which considers an information spreading model, combines it with cascades and social behavior analysis. We propose a new hybrid usage approach to represent a real-world modelling for information spreading process.

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The Sixth International Conference on Data Analytics, November 12 - 16, 2017, Barcelona, Spain

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Social network analysis, Information spreading, Information cascades

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23

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27
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9294

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224

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