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Comput Soc Netw. 2016;3(1):11. doi: 10.1186/s40649-016-0036-9. Epub 2016 Dec 7.

Detection of strong attractors in social media networks.

Author information

1
Computer Science Institute, University of Applied Science Ruhr West, Lützowstraße 5, 46236 Bottrop, Germany.
2
Department of Computer Science and Applied Cognitive Science, University of Duisburg-Essen, Lotharstraße 63, 47057 Duisburg, Germany.

Abstract

Background:

Detection of influential actors in social media such as Twitter or Facebook plays an important role for improving the quality and efficiency of work and services in many fields such as education and marketing.

Methods:

The work described here aims to introduce a new approach that characterizes the influence of actors by the strength of attracting new active members into a networked community. We present a model of influence of an actor that is based on the attractiveness of the actor in terms of the number of other new actors with which he or she has established relations over time.

Results:

We have used this concept and measure of influence to determine optimal seeds in a simulation of influence maximization using two empirically collected social networks for the underlying graphs.

Conclusions:

Our empirical results on the datasets demonstrate that our measure stands out as a useful measure to define the attractors comparing to the other influence measures.

KEYWORDS:

Asterisk; Detection of attractors; Independent cascade model; Information diffusion; Social media networks; Twitter

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