TY  - JOUR
U1  - Zeitschriftenartikel, wissenschaftlich - begutachtet (reviewed)
A1  - Qasem, Ziyaad
A1  - Jansen, Marc
A1  - Hecking, Tobias
A1  - Hoppe, Heinz Ulrich
T1  - Detection of strong attractors in social  media networks
JF  - Computational Social Networks
N2  - 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.
Y1  - 2016
UN  - https://nbn-resolving.org/urn:nbn:de:hbz:1393-opus4-1690
UR  - https://link.springer.com/article/10.1186/s40649-016-0036-9
SN  - 2197-4314
SS  - 2197-4314
U6  - https://doi.org/10.1186/s40649-016-0036-9
DO  - https://doi.org/10.1186/s40649-016-0036-9
VL  - 3
IS  - 1
SP  - 1
EP  - 21
ER  -