Abstract

In this paper, we propose a new scale-free social networks (SNs) evolution model that is based on homophily combined with preferential attachments. Our model enables the SN researchers to generate SN synthetic data for the evaluation of multi-facet SN models that are dependent on users’ attributes and similarities. Homophily is one of the key factors for interactive relationship formation in SN. The synthetic graph generated by our model is scale-invariant and has symmetric relationships. The model is dynamic and sustainable to changes in input parameters, such as number of nodes and nodes’ attributes, by conserving its structural properties. Simulation and evaluation of models for large-scale SN applications need large datasets. One way to get SN data is to generate synthetic data by using SN evolution models. Various SN evolution models are proposed to approximate the real-life SN graphs in previous research. These models are based on SN structural properties such as preferential attachment. The data generated by these models is suitable to evaluate SN models that are structure dependent but not suitable to evaluate models which depend on the SN users’ attributes and similarities. In our proposed model, users’ attributes and similarities are utilized to synthesize SN graphs. We evaluated the resultant synthetic graph by analyzing its structural properties. In addition, we validated our model by comparing its measures with the publicly available real-life SN datasets and previous SN evolution models. Simulation results show our resultant graph to be a close representation of real-life SN graphs with users’ attributes.

Highlights

  • Online social networks (OSNs) have experienced dramatic growth, due to recent advancements in information and communication technologies

  • In order to deal with the limitations of topological evaluation models, we propose a novel evolution model based on the principal of homophily and preferential attachment by considering user attribute similarity as the basis for the connection formation in SN

  • We evaluated our model by generating a synthetic SN graph, based on homophily and preferential attachment

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Summary

Introduction

Online social networks (OSNs) have experienced dramatic growth, due to recent advancements in information and communication technologies. The SN topology based evolution models produce synthetic networks that can structurally represent real-life SN and can be useful to evaluate topology based models and applications, such as modularity based community clustering [11], influence modeling [12], and information diffusion modeling [13] These evaluation models are not suitable for applications where users’ attributes and the relationship strengths are critical, such as recommendation systems [14], trust models [15], and interest-based models [16]. In order to deal with the limitations of topological evaluation models, we propose a novel evolution model based on the principal of homophily and preferential attachment by considering user attribute similarity as the basis for the connection formation in SN.

Background and Related Work
Social Network Topology Based Evolution Modelling
Homophily Based Social Network Evolution Modeling
Social Network Synthetic Graph Generation
Challenges in Synthetic Network Generation
Preliminaries
Proposed SN Evaluation Model
Evaluation and Simulation Results
Conclusions
Full Text
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