Strength prominence index: a link prediction method in fuzzy social network
Link prediction is a field within social network studies that aims to forecast future connections based on the structure of a social network. This paper introduces a link prediction method based on the strength and prominence of seed node pairs, referred to as the strength prominence index. In this method, we get a consistent score for any pair of nodes, regardless of whether they share a common neighbour. Several key characteristics have been identified. In our experiments, we used three well-known estimators to evaluate the accuracy of link prediction algorithms: precision, area under the precision-recall curve, and area under the receiver operating characteristic curve. A comparative study with existing methods is also presented, supported by relevant graphs and tables. Validation using Facebook data sets demonstrates the effectiveness of the proposed method.
Authors
- Antonios Kalampakas (ORCID: https://orcid.org/0000-0001-8821-6102)
- Sakshi Dev Pandey (ORCID: https://orcid.org/0000-0003-1258-9070)
- Leo Mršić (ORCID: https://orcid.org/0000-0002-5093-3453)
- A. S. Ranadive (ORCID: https://orcid.org/0000-0002-6352-9142)
- Sovan Samanta (ORCID: https://orcid.org/0000-0003-3200-8990)
- Tofigh Allahviranloo (ORCID: https://orcid.org/0000-0002-3929-9762)
Institutions
- Guru Ghasidas Vishwavidyalaya (IN)
- American University of the Middle East (KW)
- Higher Education Centre Novo Mesto (SI)
- Algebra Bernays University (HR)
- Istinye University (TR)
Publication Details
- Journal
- Complex & Intelligent Systems
- Published
- 2025-05-29
- DOI
- https://doi.org/10.1007/s40747-025-01925-6
- Citations
- 2
- Primary Topic
- Complex Network Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 2.65