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Detection of strong attractors in social media networks
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 charact...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5749172/ https://www.ncbi.nlm.nih.gov/pubmed/29355206 http://dx.doi.org/10.1186/s40649-016-0036-9 |
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author | Qasem, Ziyaad Jansen, Marc Hecking, Tobias Hoppe, H. Ulrich |
author_facet | Qasem, Ziyaad Jansen, Marc Hecking, Tobias Hoppe, H. Ulrich |
author_sort | Qasem, Ziyaad |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5749172 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-57491722018-01-19 Detection of strong attractors in social media networks Qasem, Ziyaad Jansen, Marc Hecking, Tobias Hoppe, H. Ulrich Comput Soc Netw Research 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. Springer International Publishing 2016-12-07 2016 /pmc/articles/PMC5749172/ /pubmed/29355206 http://dx.doi.org/10.1186/s40649-016-0036-9 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Research Qasem, Ziyaad Jansen, Marc Hecking, Tobias Hoppe, H. Ulrich Detection of strong attractors in social media networks |
title | Detection of strong attractors in social media networks |
title_full | Detection of strong attractors in social media networks |
title_fullStr | Detection of strong attractors in social media networks |
title_full_unstemmed | Detection of strong attractors in social media networks |
title_short | Detection of strong attractors in social media networks |
title_sort | detection of strong attractors in social media networks |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5749172/ https://www.ncbi.nlm.nih.gov/pubmed/29355206 http://dx.doi.org/10.1186/s40649-016-0036-9 |
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