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Social Network Analysis and Mining
Published in:

01-12-2016 | Original Article

An empirical comparison of influence measurements for social network analysis

Authors: Khaled Almgren, Jeongkyu Lee

Published in: Social Network Analysis and Mining | Issue 1/2016

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Abstract

The studying of social influence can be used to understand and solve many complicated problems in social network analysis such as predicting influential users. This paper focuses on the problem of predicting influential users on social networks. We introduce a three-level hierarchy that classifies the influence measurements. The hierarchy categorizes the influence measurements by three folds, i.e., models, types and algorithms. Using this hierarchy, we classify the existing influence measurements. We further compare them based on an empirical analysis in terms of performance, accuracy and correlation using datasets from two different social networks to investigate the feasibility of influence measurements. Our results show that predicting influential users does not only depend on the influence measurements but also on the nature of social networks. Our goal is to introduce a standardized baseline for the problem of predicting influential users on social networks.
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Appendix
Available only for authorised users
Footnotes
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Metadata
Title
An empirical comparison of influence measurements for social network analysis
Authors
Khaled Almgren
Jeongkyu Lee
Publication date
01-12-2016
Publisher
Springer Vienna
Published in
Social Network Analysis and Mining / Issue 1/2016
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-016-0360-y

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